Integrated student-growth platform

ABSTRACT

Some embodiments of an integrated student-growth platform for discovering, designating, and organizing heterogeneous instructional electronic resources based on observational assessments of students are disclosed. The student-growth platform is configured to establish and generate the best possible set of skills and resources for an educator to teach a group of students on a particular day and for a student to quickly progress to meet preferred educational standards. In one embodiment, the student-growth system includes a communication unit for sending and receiving data among users (e.g., teachers and students), an assessment platform, a planning platform, a learning-progression platform, an assignment platform, a mastery-maker platform, a Multi-Dimensional Response Item (MIRT) platform, and a reporting platform. The assessment platform  220  collects observation data for a target student, identifies one or more indicators to the learning-progression platform, which is coupled to the assignment platform, the mastery-maker platform, the MIRT platform, and the reporting module.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/086,733, titled “Integrated Student-Grown Platform,” filed on Nov. 2,2020, which is a continuation of U.S. patent application Ser. No.15/483,976, titled “Integrated Student-Growth Platform,” filed on Apr.10, 2017, which claims the benefit under 35 U.S.C. § 119(e) of U.S.Provisional Patent Application No. 62/320,595, titled “System and Methodfor the Discovery and Organization of Heterogeneous InstructionalResources to Optimize Student Growth,” filed on Apr. 10, 2016, thecontents of all of which are incorporated herein by reference in theirentireties.

BACKGROUND 1. Field of the Invention

The present invention relates to systems and methods for use in learningin an educational environment. More particularly, the present inventionrelates to an integrated architecture for a student-growth platform foruse in an educational environment for the discovery and organization ofheterogeneous instructional resources to optimize student growth anddevelopment in an online, cloud-based environment. This student-growthplatform provides the ability to surround the instructional process, atany level (district, state, national, or global) with growth-optimizingoptions and integrates assessment, teaching, and learning-solutionoperations for students and educators.

2. Description of the Related Art

Teachers are continually faced with the problem and challenges ofplanning lessons before teaching students. It is estimated that teacherstoday can spend as much as seven to ten hours per week assembling lessonplans.

With digital instruction on the rise, within the last twenty years, thislesson-planning exercise has become quite an ordeal for teachers. In thepast, teachers often relied on a printed textbook to impart from andorganize student learning. Yet, with the increasing use of digitalresources, teachers have an increasing desire to build lesson planstypically involving a combination of core curriculum, supplementalresources, and ad hoc internet-based resources (OERs). However,searching for, finding and organizing instructional resources into anefficacious and differentiated lesson plan that varies and is tailoredto individual students has become a daunting task. As the digitaluniverse of educational content expands and the complexity of digitalcurriculums increases, the lesson-planning exercise only becomes morechallenging and time consuming every day.

Research reveals that the lesson-planning exercise and ordeal consumesat least seven to ten hours weekly. In many teaching scenarios, teachersbuild lesson plans by using ad hoc variations of a seven-step workflowwith each step typically relying on a distinct tool such as MS Excel,Google, and pen & paper. The typical seven-step workflow includes: 1)review student data (50 minutes); 2) identify learning objectives usinga pacing guide (20 minutes); 3) prepare to teach this week's skills orconcepts (25 minutes); 4) search for instructional resources (45minutes); 5) create homework (50 minutes); 6) find or build assessments(90 minutes); and 7) create assignments (50 minutes).

Existing digital instruction technology is unable to help teachers,bridge the gap from use of assessment data to identifying particularskills that a particular student or student group is ready to learn. Norcan it use those target skills to first identify relevant instructionalresources and then, to organize those resources to optimize andaccelerate student learning, growth, and performance toward achievingacademic excellence. Previous solutions were inadequate or deficient andare solved by the present technology.

SUMMARY

The present technology created overcomes the deficiencies andlimitations of prior systems and methods, at least in part by, providingan integrated learning and student-growth platform with improved systemsand methods for discovery, organization and prescription ofheterogeneous instructional resources for student learning anddevelopment.

The student-growth platform instantiates a closed-loop system acceptingteacher context (including a chosen curriculum), and student context(including assessment) and automatically generating an output with adigital lesson plan. In some embodiments, the closed-loop system, globalin scope, comprises five fundamental elements: 1) a growth-projectionengine or platform; 2) a universal-skills-pool engine or platform; 3) acurriculum-to-skills-mapper engine or platform; 4) agrowth-optimizing-instructional-resource-recommendation engine orplatform; and 5) a lesson-planning platform.

In accordance with one aspect of the invention, the student-growthplatform uses a student growth percentile (SGP) algorithm to uniquelyposition a target student or a target group of students into a scaledlearning progression scheme based on the amount of time elapsed sincethe last set of assessments for the target student or the target groupof students. In some implementations, this SGP algorithm may beimplemented by a scaled learning-progression engine, which determines ifparticular students fall into a particular group, a class, a group ofclasses, a school, a group of schools, a district, or a state.

In accordance with another aspect of the invention, the student-growthplatform has a system and method adapted to establish the best possibleset of skills to teach a group of students on a particular day. Thissystem and method combines computer-adapted testing(CAT)+student-growth-percentile (SGP)+time-based projection+entry pointsto establish curriculum entry point.

In accordance with yet another aspect, the student growth system has amastery-model system that is adapted to combine a student's CAT scoreswith practice scores and evaluate the combined score against a learningprogression scheme. This innovation focuses on normalizingcomputer-adapted testing outcomes (GOMs) with practice assignments tocreate an integrated model of mastery, which may be evaluated against alearning progression scheme.

In accordance with yet another aspect, the student-growth platform has amastery model, extended by an inferencing capability. The integratedmastery model extends actual testing, by using intelligent inferencingcapability, based on determining the relationship of objects within thelearning progression scheme.

In accordance with yet another aspect, the student-growth platformutilizes a universal-skills-pool to enable curriculum mapping. Thisfeature, system, or method facilitates lesson planning by mapping to theteacher's chosen curriculum, pacing guide, or text book. Skills may bedivided by domains. In some embodiments skills may be divided into fourdomains including foundational skills, language, literature,informational text.

In accordance with yet another aspect, the student-platform has a sevenstep planning engine, which is a lesson-planning engine that mirrors orsimulates a teacher's complete process by providing ascore-to-skill-to-resource-to-assignment-to-plan-management process.

In accordance with yet another aspect, the student-growth platform has amulti-dimensional-response-item (MIRT) model that is utilized to bindassignments from assessment, instruction, and practice assignments intoa unified scale that supports the other aspects of the student-growthplatform.

In accordance with yet another aspect, the student-growth platform has afour level mastery model supporting lesson planning that has the abilityto view mastery by assignment source, by probed assessment, by generaloutcome measurement (GOM) assessment, and by an integrated model.

In accordance with yet another aspect, the student-growth platform usesa universal skills pool to bridge from a GOM to a range of curriculums.This feature or system enables the lesson planning engine to act as aRosetta Stone or like language capability for automatically linkingmultiple assessments to multiple government-created learning standards.

In accordance with yet another aspect, the student growth system orplatform has a mechanism for probabilistic mastery, by whichprobabilistic algorithms are incorporated into the student-growthplatform.

In accordance with yet another aspect, the student-growth platform hasan open-lesson planning eco-system, by which the lesson planning processweaves into many different assessment sources with many differentstandards, curriculums, instructional resources, and assignment deliverysystems.

The system and methods disclosed here are advantageous in a number ofrespects. They provide a significant improvement over existing systemsand other solutions that exist. The integrated student-growth platformenables successful competition with “Assessment” vendors that lack theability to create a complete feedback loop, and “Practice” vendors, wholack assessment functionality. The student-growth platform is global inscope and enables any education company or organization in the world tobuild a network-effect based category that spans separate markets in“ed-tech” today. The innovative approach of the instant technology iscombined with unique access to student data to provide significantcompetitive advantages. This cutting edge approach of the student-growthplatform may be implemented by a single source implementation, animplementation with assignment generation, and/or an implementation withcurriculum mapping.

The student-growth platform in accordance with the present inventionadvantageously solves four significant problems that have in the pastdefeated other attempts to create a system for organizing resources intogrowth-optimizing lesson plans. The first is management of heterogeneousresources. Lesson planning solutions so far have typically focused onutilizing resources from one or a small number of sources. By using arecommendation engine coupled to a universal-skills-pool engine, thestudent-learning- and growth platform allows teachers or educators toemploy almost any IR in their lesson plan.

The second is that teachers must bring their own instruction. Teachersuse a wide range of curriculums (text books, core instructionalsoftware, and pacing guides) to provide the frame for lesson planning.Most solutions either ignore the teacher's chosen curriculum or requirethe teacher to abandon that solution and employ a different scope &sequence of skills instruction embedded into the solution. Thestudent-learning-and-growth platform advantageously allows teachers toutilize their chosen curriculum in the planning process, regardless ofwhat curriculum they've chosen.

The third advantage is planning from projected growth data. Most lessonplanning proceeds from a point of either no data available or fromobservation of assessment information that is not current. Lessonplanning is typically performed weekly and often with even greaterfrequency. The student-learning-and-growth platform has agrowth-projection engine that translates assessment data into anactionable planning template, building a valid bridge from historicalassessments on a student to a student's zone of proximal development(ZPD) in a short time.

The fourth advantage is the automated workflow. Lesson planningsolutions so far have failed to mirror the full end-to-end processemployed by teachers. As a consequence, they have not deliveredmeaningful reduction in teacher time spent in planning lessons.

Other innovative aspects include corresponding systems, methods,apparatus, and computer program products.

It should be noted that the language used in the present disclosure hasbeen principally selected for readability and instructional purposes,and not to limit the scope of the subject matter disclosed herein.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example, and not by wayof limitation in the figures of the accompanying drawings in which likereference numerals are used to refer to the same or similar elements.

FIG. 1A is a high-level block diagram illustrating a networkeddistributed environment including user/client devices for use by users(e.g., students, teachers, etc.) coupled to an integrated student-growthplatform including different platforms with specific functions anddedicated to specific operations for educational use.

FIG. 1B is a high-level block diagram illustrating an alternativeembodiment of the distributed environment illustrated in FIG. 1A.

FIG. 2A is a block diagram illustrating example assessment and planningplatforms within the integrated student-growth platform illustrated inFIG. 1A.

FIG. 2B is a block diagram illustrating example assignment and reportingplatforms within the integrated student-growth platform.

FIG. 3 is a block diagram illustrating an example integratedstudent-growth platform with integrated assessment, planning,assignment, reporting coupled to the learning-progression engine, themaster-maker engine and other elements of the platform.

FIG. 4 is a block diagram of the example integrated student-growthplatform illustrating its example hardware units including data storage.

FIG. 5 is an example hardware configuration of an example user devicethat interacts with the student-growth platform.

FIG. 6 is a flow chart illustrating an example overall method of studentgrowth according to a prescribed plan generated by the student-growthplatform.

FIG. 7 is a flow chart illustrating an example method of assessment.

FIG. 8 is a flow chart illustrating an example method of a prescribedplan generated by the student-growth platform.

FIG. 9 is a flow chart illustrating an example method of prescribingassignments.

FIGS. 10 and 11 are a flow chart illustrating an example method ofreporting by the student-growth platform.

FIG. 12 is a flow chart illustrating an example method of determiningelectronic resources and associating them with the assignment.

FIG. 13 is a flow chart illustrating an example method for reporting.

FIG. 14 is a observational graphic interface generated by thestudent-growth platform.

DETAILED DESCRIPTION

The systems and methods of this technology are directed to systemarchitecture, technical platforms (e.g., to facilitate and linkeducational activities involving input and output by different users)and methods configured to facilitate student growth and development, byproviding an integrated student-growth platform with technical tools foruse in an online, cloud-based environment, for improving the educationalprocess. This integrated student-growth platform provides acomprehensive view of student growth and mastery available foreducators, by its observational interface, accessible to users orclients. This integrated student-growth platform addresses the problemsthat educators have faced so far, on how to accurately measure andmonitor student growth and performance on a daily basis, as well as,differentiate and personalize instruction to each student. Theintegrated student-growth platform in accordance with the presentinvention permits educators to set goals and monitor student progresswith greater efficiency. This integrated student-growth platformincludes a workflow engine that allows educators (e.g., teachers) tomanage and deliver all assignments from assignment engines to subjectpractices through a simple-to-use student inbox. This student-growthplatform provides educators with a comprehensive view of student growthand mastery while giving them more time to focus on students. Thestudent-growth platform fully integrates learning analytics to makedecisions and lay the groundwork for increased interoperability withexisting school systems and instructional partners.

FIG. 1A illustrates a general distributed environment (e.g.,cloud-based) as designated generally by reference numeral 100 a, withusers 114 a, 114 b, through 114 n, using user/client devices, 106 a, 106b, through 106 n, and interacting with an integratedstudent-learning-and-growth platform 118, via a network 102. Each of theuser devices may have a user application 108 a. User/clientcommunications flow via lines 112 a, 112 b, through 112 n, respectively,to the user devices, 106 a, 106 b, through 106 n, and through lines 104a, 104 b, through 104 n, to the network 102 and through line 116 to thestudent-learning-and-growth platform 118. The integratedstudent-learning-growth platform 118 integrates functionalities ofvarious platforms, including but not limited to, an assessment platform220, a planning platform 222, a learning-progression platform 224, anassignment platform 226, a mastery-maker platform 228, a MIRT(multi-dimensional-response) platform 230, and a reporting platform 232.Access to each of these platforms is accomplished via an observationengine 221, which is a part of the user interface of the student-growthplatform 118. Such platforms facilitate digital reading and enablecollaboration in and with the pages of digital books, articles, anddocuments, enabling users to embed materials and assignments in the textitself or attach them and provide them separately. They facilitateattaching highlight and tag functions to a piece or portion of text in asingle action or activity. In some implementations, the text of interestor display for use in assessment, lesson planning, or any other taskdescribed here may be a digital book, an electronic article, or anyother available text content presented by a suitable electronic device.In some examples, the text may be the text content on a page of adigital book available on the web or downloaded as an ePub (electronicpublication) or PDF (portable document format).

The integrated student-growth platform 118 may include one or moreservers with one or more processors and one or more storage devicesstoring data or instructions executable by the one or more processors.For example, the integrated student-growth platform 118 may be a server,a server array or any other computing device, or group of computingdevices, having data processing, storing and communication capabilities.The integrated student-growth platform 118 may be a virtual server(i.e., a virtual machine) implemented via software. For example, thevirtual server operates in a host server environment and accesses thephysical hardware of the host server including, for example, aprocessor, memory, storage, network interfaces, etc., via an abstractionlayer (e.g., a virtual machine manager). It should be understood thatthe integrated student-growth platform 118 may be made up of anycombination of devices and servers, or only one device or server. Theintegrated student-growth platform 118 may interact with the userdevices 106 a-106 n or other third-party servers 117 ormedia-distribution servers 115, media store 111, or data stores 113 athrough 113 n, of the distributed system 100 a, via the network 102, ormay be coupled to and interact with any of these entities via a directdata connection.

In some embodiments, the entities of the distributed system 100 aincluding the integrated student-growth platform 118 and themedia-distribution server 115 may be implemented using cloud-basedarchitectures where one or more computer functions are performed byremote computing systems and devices at the request of a local computerdevice. For example, a user/client device 106 a may be a computingdevice having a limited set of hardware and/or software resources andmay access hardware and/or software resources provided across thenetwork 102 by other computer devices and resources, such as other userdevices 106 b, the third-party server 117, the integrated student-growthplatform 118, or any other computing resources. The user/client device106 a may access these resources through a user application 108 a, suchas a web browser or customized application, and the results of anycomputer functions or resources may be delivered through the userapplication 108 a to the user/client by the user device 106 a, such asthose described. The integrated student-growth platform 118 may be acloud-based distributed computing system having dynamically scalable andvirtualizable resources, and various functionality of the integratedstudent-growth platform 118, including the functionality of theassessment platform 220, the planning platform 222, thelearning-progression platform 224, the assignment platform 226, themastery-maker platform 228, the multi-dimensional-response platform 230,and the reporting platform 232 and/or the media-distribution server 115may be carried out and supplemented by computing systems and devicesdistributed over the network 102. Although only one integratedstudent-learning-and-growth platform 118 is shown, multipleservers/platforms 118 may be included in the system 100 a for regionalor global reach or for specific purposes.

The media-distribution server 115 is a computing device and/or systemfor transmitting electronic resources stored in or available through themedia data store 111 to the other entities of the environment 100 a. Insome embodiments, the media-distribution server 11 cooperates with theintegrated student-growth platform 118 to provide an electronic resourceto a user (e.g., teacher or student) for consumption. For example, theassessment platform 220 or the assignment platform 228 of the integratedstudent-growth platform may transmit a file (e.g., a webpage) to auser/client device 106 for display to the user/client 114. In someinstances, the file may include code (e.g., a video player) executableto receive a video and/or audio stream (e.g., an electronic resource)from the media distribution server 115 and render it for display to theuser/client. In other embodiments, the integrated student-growthplatform 118 performs the function of the media-distribution server 115.In the depicted embodiment, the media-distribution server 115 is coupledto the network 102 via signal line 123 for communication with the otherentities of the environment 100. The media-distribution server 115 isalso coupled to the media store 111 to access electronic resources andother data stored in the media store 111. In some embodiments, themedia-distribution server 115 is a hardware server including aprocessor, memory and network communication capabilities. In otherembodiments, the media-distribution server 115 is a virtual server.

In some embodiments, the media-distribution server 115 transmits videoand audio streams to one or more user/client devices 106 a-n. The videoand audio streams may be live feeds or may be previously recorded,stored as media objects in the media store 111, and transmitted to theone or more user/client devices 106 a-n on demand, via delayedbroadcast, etc. In some embodiments, the audio and video are streamedfrom the media-distribution server 115 via the network 102. In otherembodiments, a user/client can download an instance of the video andaudio media objects from the media-distribution server 115 to a localrepository for storage and local playback.

The media-distribution server 115 and/or the integrated student-growthplatform 118 is/are capable of transmitting any number of electronicresources to any number of user/client devices 106 a-n simultaneously.While in the illustrated embodiment, only one media-distribution server115 is shown, any number of media-distribution servers 115 and/or mediastores 111 may be included in the distributed environment. For example,the media-distribution server 115 and the media store 111 may be adistributed server and storage system with local instances strategicallylocated in locations where spikes in demand for the electronic resourcesare likely to occur. For example, if a cluster of user/client devices106 a-n are located in a particular geographic region, local instancesof the media-distribution server 115 and the media store 111 may becoupled to the network 102 in that geographic region such that the mediaobjects stored in the media store 111 may be served locally and at afaster data rate to that cluster of user/client devices 106 a-n.

It should be understood that, in some embodiments, themedia-distribution server 115 and/or the third-party server 117 have thesame or similar architecture (e.g., memory, processor, communicationunit, bus, etc.) as the integrated student-growth platform 118illustrated in FIG. 2 , and thus the description of those componentsapplies to the media-distribution server 11 and/or the third-partyserver 117.

The media store 111 is an information source for storing data andproviding access to stored data. The stored data may include theelectronic resources described above, such as media objects includingvideo, audio, vector-based files, electronic books, documents, etc. Insome embodiments, the media store 111 is included in the memory (notshown) of the media-distribution server 115. In other embodiments themedia store 111 is included in the memory 404 (see FIG. 4 ) of theintegrated student-learning-and-growth platform. In yet otherembodiments, the media store 111 is included in a server or storagesystem distinct from but accessible by the media-distribution server 115and the integrated student-learning-and-growth platform. In someembodiments, the media store 111 includes a database management system(DBMS) executable by a processor to manage a collection of records,files, and objects including the media objects. For example, thedatabase could be a structured query language (SQL) DBMS. In theseembodiments, the integrated student-learning-and-growth platform 118and/or the media-distribution server 115 are coupled to a data store 113a through 113 n, via the bus 406 to store data in multi-dimensionaltables having rows and columns, and manipulate, i.e., insert, query,update and/or delete, rows of data using programmatic operations (e.g.,SQL queries and statements).

The third-party server 117 is a server hosting a network-based softwareapplication operable to provide various services or functionalities, andto send data to and receive data from the integratedstudent-learning-and-growth platform 118, the media-distribution server115, and the client devices 106 a . . . 106 n via the network 102. Inthe depicted embodiment, the third-party server 1117 is coupled to thenetwork 102 via signal line 125 for communication with the otherentities of the system 100. The third-party server 117 is also coupledto the data stores 113 a-113 n by signal lines 121 a and 121 n foraccessing and storing data. In some embodiments, the third-party server117 is a server, server array or any other computing device, or group ofcomputing devices, having data processing, storing and communicationcapabilities. In other embodiments, third-party server 117 is a virtualserver.

The third-party server 117 can provide access to data stored in the datastore 113 a-113 n that is associated with users of the integratedstudent-learning-and-growth platform 118. In some embodiments, the datastored in the data store 113 a-113 n may include demographics data,achievement data, student data, teacher data, standards data,inter-rater reliability data, etc., and the third-party server 117 mayinclude a software application for providing secure access to this datato the integrated student-learning-and-growth platform 118 over thenetwork 102 via an API. For example, in an educational setting, thedemographics data may include instructor and pupil demographics data,and may be segmented across school district, school, classroom, grade,etc.; the achievement data may include standardized test scores foreducators and pupils; the student data may include student assessmentsof teachers (e.g., aggregated from surveys, reviews, etc.), biographicaldata describing the students, social graph data (e.g., aggregated fromthird-party social networking services), etc.; the teacher data mayinclude biographical data describing the teachers, social graph data(e.g., aggregated from third-party social networking services), teacherpreferences, teacher assessments of students (e.g., aggregated fromsurveys, reviews, etc.), etc.; and the standards data may includestandards compiled and approved by a governing organization orinstitution which define the levels of attainment pupils much reach tobe considered acceptably educated. It should be recognized that thefifty states in the U.S. may have unique needs and standards foreducation. The standards may require a varying range of skills. In someembodiments, a local instance of the data stored in the data store 113a-113 n may be included in the data store 113 a-113 n. For example, abatch program operating periodically (every few minutes, hours, days,weeks, etc.) may retrieve a refreshed version of the data stored in thedata store 113 a-113 n.

In FIG. 1A, the integrated student-learning-and-growth platform 118includes an user-interface unit 119, an observation engine 221, anassessment platform 220, a planning platform 222, a learning-progressionplatform 224, an assignment platform 226, a mastery-maker platform 228,a multi-dimensional response platform 230, and a reporting platform 232.The assessment engine 220 is software including routines for providingnetwork-based assessment of students.

In some embodiments, the integrated student-learning-and-growth platform118 may collect and store mapping information (i.e., social graphs) inthe data store 113 a-113 n mapping how all users 106 a-106 n of theintegrated student-learning-and-growth platform 118 are associated. Forexample, the social graph of each user may describe that user's 114 arelationships with other users 114 n, based at least in part on sharedattributes, etc. All users 114 a-114 n may be associated by school,school district, subject matter taught, amount of experience, etc. Usersmay also define their own connections and sets of users usingfunctionality provided by the client application 108 in cooperation withthe integrated student-learning-and-growth platform 118. For example,users 114 a-114 n sharing a similar subject matter may add one anotherto their community by using functionality provided by the clientapplication 108 a in cooperation with the integratedstudent-learning-and-growth platform 118. The integratedstudent-learning-and-growth platform 118 may also generate and maintaina user profile in the data store 113 a-113 n for each user of theintegrated student-learning-and-growth platform 118. A user profile is acollection of personal and student/teacher/administrator data that isunique to a specific user. In some embodiments, the user profile is adigital representation of that person on a student/teacher/administratordevelopment service and includes a user's customized settings andpreferences, biographical information, schooling information, personalinterests, teacher/administrator information, lesson-plan developmentinformation, social connection information, etc.

In some embodiments, access to the integratedstudent-learning-and-growth platform 118 via the network 102 may beprovided to teachers and administrators in an academic environment orother educational setting, such as a school district. Instruction may beprovided by electronic resources.

An electronic resource may be any electronic media for conveyinginformation. For example, an electronic resource can be instructional innature, and can convey knowledge, information, and resources to a userwho interacts with or views it. As a further example, an electronicresources may include an instructional audio or video segment, apublication, an interactive instructional reference, a lesson plan, aplanning tool, a community forum, a sharing tool, an industry standard,a portfolio tool, a progress monitoring tool, a reporting tool, etc. Insome embodiments, an electronic resource can include any of texturaldata, graphical data, video data, audio data, etc. For example, theelectronic resource may be a webpage including one or more of text,graphics, video, audio, etc. In another example, the electronic resourcemay be or include a downloadable or streamable media object, including,for example, an electronic document (e.g., portable document format(PDF) document), electronic book (e-book), digital video, digital audiofile, vector graphics file, etc. In these or other examples, theelectronic resource may include a dataset/electronic file with text,graphics, video, audio, etc. embedded therein.

In some embodiments, these electronic resources may convey informationon various topics, such as student training, teaching skills, andsimilar subjects of consequence and importance to the growth anddevelopment of the users. For instance, for teachers an electronicresource may be an instructional video about an aspect of teaching, anda teacher may view the video by streaming it using his/her client device106. In another example, the electronic resource may be a web-basedinteractive reference including text, audio, video, etc., and theteacher may study the reference by interacting with it via a clientapplication 106 such as a web browser before determining that it isappropriate for a particular student, student group or a particularlesson plan.

FIG. 1B illustrates an alternative embodiment including agrowth-projection engine 101 connected through the network 102 to auniversal-skills pool 103, a curriculum-to-skills mapper 105, aninstructional-resource-recommendation engine 107, a lesson-planningengine 109, and the media store 111, a data store 113 a-113 n,media-distribution server 115 and the third-party server 117. Asillustrated here, the student-growth platform instantiates a closed-loopsystem accepting an input of teacher context (including a chosencurriculum) and an input of student context (including assessment) andautomatically generating an output with a digital lesson plan. Theclosed-loop system, global in scope, may be tailored by institution oreducational intent and comprises at least five fundamentalcomponents: 1) a growth-projection engine 101; 2) auniversal-skills-pool engine 103; 3) a curriculum-to-skills-mapperengine 105; 4) an instructional-resource recommendation engine 107; and5) a lesson-planning engine 109.

The student-growth system has a unique student growth percentilealgorithm (SGP) to selectively position a student or a group of studentsinto a scaled learning progression scheme, based on the amount of timethat has elapsed since observation of the last set of assessments on aparticular student. In some implementations, this unique SGP algorithmmay be implemented by a scaled learning progression schemes (similar tothose used by the learning-progression platform in FIG. 1A), which maydetermine if students fall into a particular group, a class, a group ofclasses, a school, a group of schools, a district, or a state. Thelearning-progression schemes are adapted to establish the best possibleset of skills to teach a group of students on a particular day. Thiscombines the CAT (Computer Adapted Testing)+SGP (Student GrowthPercentile)+time-based projection+entry points to establish curriculumentry point. The universal-skills pool engine 103 bridges from a GOM toa range of curriculums. This feature enables the lesson-planning engine109 to act as a Rosetta Stone or like language capability for linkingmany assessments to many government-created learning standards.

After a user (e.g., educator or teacher) selects the learning objectives(skills) and chooses to build a lesson plan, by the lesson-planningengine 109, the user/client 106 may choose the student resources andassessments to include in the lesson plan for each group. Resources mayinclude sample items, worked examples, videos, lessons, definitions, oractivities. Assessments include assessment probes designed to evaluate alevel of skills. As a user selects resources and assessments, they maybe assigned to student groups.

When a teacher generates a lesson plan, students automatically see theresources and assessments in the assignments list on their home pageonce the lesson plan begins. At the top of the add resources andassessments page, the teacher sees the learning objectives (skills) thatwas selected. If the teacher wants to concentrate on resources andassessments for one skill at a time, only that skill may be checked. Theteacher may easily change which skills are checked as the teacher addsresources and assessments. If the teacher choses more than three skills,the teacher may use the scroll bar to see the rest of the skills.Resources and assessments that are related to the checked skills arealready listed on the page. The template may be configured to showcolored squares for each resource or assessment to show the viewer whichof the skills it relates to. For example, in one example, the colorsshow the viewer that the resource is for the second skill.

For the purposes of this disclosure, it should be recognized thateducation has many standards and preferences that must be met in aparticular country, state, or district. For example, the common corestate standards initiative in the U.S. is an educational initiative thatdetails what K-12 students should know in English language arts andmathematics at the end of each grade. This initiative seeks to establishconsistent educational standards across the states as well as ensurethat students graduating from high school are prepared to entercredit-bearing courses at two or four-year college programs to enter theworkforce. The student-growth platform 118 approaches studentdevelopment based on a universal-skills pool approach that is madeavailable through learning progression schemes. This approach is basedon selecting a range of skills that are appropriate for a specific scalescore accorded to a student or group of students. A scale score deliversor specifies an entry point into the learning progression schemes thatrepresents the student's “zone of engagement.” This zone of engagementincludes a range of skills that the student is more likely to be readyto learn. This improves the accuracy of the data and insights that areprovided to teachers to inform their instruction. The planner (e.g.teacher) permits aligning learning progressions to pacing guides,district curriculum, and textbooks. This makes the learning progression(by subject) more useful to teachers and administrators focused on acurriculum and not just a standard.

Referring now to FIGS. 2A and 3 , the assessment platform 220 of thestudent-growth platform 118 includes a computer-adapted-testing engine203, a fixed-form engine 205, an assessment-importer module 207, and auniversal-scale module 209. The assessment platform 220 as illustratedmay be accessed by district administration of an institution to obtainprevious or old assessments for a particular student or group ofstudents that may be imported by the assessment-importer module 207 fromsources that have these assessments. The universal-scale module 209receives inputs from the computer-adapted-testing engine 203, fixed-formengine 205 and the assessment-importer 207. The universal-scale module209 positions a target student into a standard scale (e.g., mandated bya governing body) based on testing data obtained from thecomputer-testing engine 203, prior data provided by a student determinedby the fixed-form engine 205, and prior assessment data imported by theassessment-importer module 207.

The planning platform 202 includes an expected-score engine 244, apacing-guide manager 246, a skills-selection engine 248, arecommendations engine 250, a resource-finder engine 252, andlesson-organizer engine 254. FIG. 2A also illustrates alearning-progression engine 236, a mastery-maker engine 238, and amulti-dimensional-response-item engine 240. In some embodiments, theplanning platform 202 is coupled to a single-source implementation 211,a multiple-source implementation 213, an assignment generation unit 215,and a curriculum mapping unit 217.

The planning platform 202 computes and expected score for a targetstudent based on where the target student is positioned (e.g., bycomparing within a range of scores for the level where the targetstudent is positioned). The pacing-guide manager 246 is softwareincluding routines for prescribing and managing the pace at which thetarget student should learn. The skills-selection engine 248 is softwareincluding routines for selecting skills appropriate for the level andpace prescribed for the target student. The recommendation engine 250 issoftware including routines for recommending instructional resources forthe target student that are consistent and appropriate for the leveldetermined and pace prescribed for the target student. Theresource-finder engine 252 is software including routines for managingand providing resources and content for students. In some embodiments,the resource-finder engine 252 catalogs the electronic resources,provides for the addition or removal of electronic resources, transmitsthe electronic resources to students for consumption, tracks userconsumption and interaction with the of electronic resources, etc.

The resource-finder engine 252 is coupled to the data store 410 (FIG. 4) and the media data store 111, either directly or via themedia-distribution server 115, to access the electronic resources storedtherein. In some embodiments, the resource-finder engine 252 can searchthe data store 410 and the media data store 111 to generate and collectinformation about the electronic resources. For instance, theresource-finder engine 252 can aggregate attributes of the electronicresources, such as the author, publisher, file size, creation date,publication date, a thumbnail of the resource, etc., and store them in aresource library database. In various embodiments, the resource-finderengine 252 can access the electronic resources in the data store 410 andthe media data store 111 to transmit or stream copies of those resourcesto the client devices 106 of the users 114 requesting to interact withthem.

The resource-finder engine 252 can also receive and store new electronicresources in the media data store 111 or the data store 410. In someembodiments, the resource-finder engine 252 may interact with themedia-distribution server 118 to store information in the media datastore 111. In other embodiments, the resource-finder engine 252 maystore information in the media store 111 directly. In some embodiments,the resource-finder engine 252 may receive resource addition requestsvia the network 102, requesting the addition of electronic resourcesaccessible to the student-growth platform 118. For example, there-source finder engine 252 is capable of serving a webpage to auser/client device 106 that provides functionality for the user of theclient device 106 to author or upload an electronic resource along withmetadata characterizing it. The electronic resource may be aninteractive electronic book, a video file, an audio file, a document, adataset, an electronic link, or any other electronic resource that canbe accessed and viewed by the observational engine 221 of via thestudent-growth platform. The resource-finder engine 252 may receive theadditional electronic resource, store the metadata about the resource inthe resource library database, and store the electronic resource in thedata store 410 and/or media data store 111. Thus, the resource-finderengine 252 can update the resource library database, either periodicallyor real-time, with any new electronic resources that have been added toor removed from the student-growth platform 118.

The resource-finder engine 252 is capable of receiving requests forelectronic resources from users 106 and fulfilling those requests bytransmitting the electronic resources to the corresponding clientdevices 106 of the users 114. In one example, upon logging in to thestudent-growth platform, a user 106 may be presented with an interfaceby the user application 108 that shows any outstanding assignments thatthe user 114 must complete, the dates by the assignments must becompleted, a description of what the assignments are, etc. Using thisinterface, the user 114 may select an assignment, in response to whichthe user application 108 transmits a request to the resource-finderengine 252 for the electronic resource associated with the assignment.In yet another example, an observer, upon logging in, may be providedwith electronic resources (e.g., video, audio, etc.) by theresource-finder engine 252 in cooperation with the client application108, which describes what to focus on, observe, evaluate, during anupcoming/pending observational assessment of a target subject. In theseor other examples, electronic resources can be identified and served tothe users based on the users' social graphs and/or preferences. Theresource-finder engine 252, upon receiving this request, may locate theelectronic resource in the data store 410 and provide it to the userapplication 108 via the network 102 for presentation to the user 114. Asdiscussed elsewhere herein, the resource-finder engine 252 may, in someembodiments, cooperate with the media-distribution server 116 to providethe electronic resources for consumption and/or interaction by the users114 requesting them.

When users consume or interact with the electronic resources provided bythe resource-finder engine 252, the resource-finder engine 202 iscapable of logging the consumption and interaction in the data store 410in association with those users. In some embodiments, theresource-finder engine 252 cooperates with the user application 108 tomonitor user interactions with the electronic resources. For example,when user interacts with a user interface generated and displayed by theuser application 108, the user application 108 sends interaction datavia the network 102 to the resource-finder engine 252 informing theresource-finder engine 252 of the interaction, and the resource-finderengine 252 stores this interaction data. In a further example, if a userinteracts with a media player embedded in a user interface of the userapplication 108, interaction data describing the user's interactions,such which actions the user took (e.g., clicked a pause button, a playbutton, a scrubbing dial, volume dial; maximized the viewing field ofthe media player; added a comment about the video using an associatedinterface element; etc.) are sent by the user application 108 to theresource-finder engine 252 and the resource-finder engine 252 may logthose interactions. The interaction data may also include or beassociated with data identifying which electronic resource wasinteracted with, the user who interacted with the resource, the time anddate of the interaction, etc. In another example, if a user is accessingan interactive electronic book, the user application can sendinteraction data describing when the user begins interacting with theelectronic book, pages through the electronic book, downloads filesincluded with or embedded in the electronic book, completes surveysincluded with the electronic book, views videos embedded in theelectronic book, comments on passages of the electronic book, orotherwise uses any other functionality provided by the user application108 for interaction with the electronic book or the correspondingcomponents of the student-growth platform 118.

In some embodiments, the resource-finder engine 252 may provide theelectronic resource to the user/client devices 106 with presentationalinformation and the client application 108 may use the presentationalinformation to form the look and feel of the user interfaces. Forexample, the electronic file(s) or data stream(s) may be formatted usinga markup language (e.g., HTML, XML, etc.), style sheets (e.g., CSS, XSL,etc.), graphics, and/or scripts (e.g., JavaScript, ActionScript, etc.),and the client application 108 may interpret the interface instructionsand render an interactive Web User Interface (WUI) for display on a userdevice 106 based thereon. In other implementations, the user/clientapplication 108 may determine the formatting and look and feel of theuser interfaces independently. Using the user interfaces presented bythe client application 108, the user can input commands selectingvarious actions.

Referring now to FIGS. 2B and 3 , the assignment platform 222illustrated with an instructional bridge 242 a and an instructionalbridge 242 b. The first instructional bridge 222 a includes a printengine 253 adapted to print assignments as needed, a scan engine 256 forscanning documents with assignments as needed, and anassignment-importer module 258 for importing or downloading assignmentsfrom other sources. The second instructional bridge 222 b has anassignment manager 260 for managing assignments given to students, agrading framework 262, by which grading of assignments is accomplished,and an assignment player 264, by which assignments are conveyed totarget students (e.g., by audio, video, or other forms of media). Thereporting platform 232 includes dashboards/dashboard services 233,alerts/alert manager 235, and an exporter 237, by which completedassignments may be exported or sent for further consideration orstoring.

In some embodiments, the user-interface unit 119 (FIG. 1 ), incooperation with the observation engine 221 (FIG. 1 ), may generate areport dashboard/interface for viewing reports generated and provided bythe reporting platform 232 and received by the observation engine 221.In some instances, the reporting platform 232 may provide diagnosticreports. This dashboard provides numerous advantages including providingan observer (e.g. teacher) or administrator with detailed informationabout a given target student's performance (e.g., execution,effectiveness, compliance, etc.) over time. For example, the observermay be a teacher using the dashboard, to access any previousobservational assessments of that student or student group; view anoverall performance (e.g., execution, effectiveness, compliance, etc.)view statistics across all observational assessments of that student ora subset, such as the observational assessments performed for thatacademic year; may quickly ascertain the areas a student has hadproblems with or has been working on, or the areas the student has beenimproving on; review the test scores for the student, view theelectronic training resources the student has consumed/interacted with;view any work-product, lesson plans, videos, presentation, etc., thestudent has uploaded, the groups the student has interacted with, etc.Using this information, the teacher may quickly get up-to-speed on wherethe student is at, thus provide pertinent and relevant observations(e.g., evaluations, ratings, suggestions, comments, etc.) andassignments, etc., during the observation session to be performed. Thealerts 235 may be adapted to generate and provide alerts depending uponcertain criteria that are specified.

Referring specifically to FIG. 3 , is should be recognized that in someexample scenarios, a district administrator 332 may have access to theassessment platform 220 to generate the assessments required. A teacher336 may have access to the planning platform 222 to plan and generatelessons and the student 334 may have access to the assignment platform226 to receive and complete assignments.

The learning progression engine 316 drives information that is conveyedin the instructional planning and diagnostic reports that are generated.Learning progressions are descriptions of how learning typicallyadvances in a subject area. Empirically based learning progressions canvisually and verbally articulate a hypothesis, or an anticipated path,of how student learning will typically move toward increasedunderstanding over time with good instruction. The learning-progressionsengine 316 has an organizational structure, separated into domains,skill areas, and core skills. For example, a core progress scenario formathematics has four domains, which form the base of the learningprogression for that subject: 1) numbers and operations, 2) algebra, 3)geometry and measurement, and 4) data analysis, statistics andprobability. The skills areas (e.g., whole numbers, place value, symbolsand expressions, time etc.) represent the various skills and conceptsstudents acquire as they progress in the development of mathematics atthe level they are prescribed. The core progress learning progression isan interconnected web of prerequisite skills. For increasedunderstanding over time, progress requires continually building up andbuilding on a solid foundation of knowledge, concepts, and skills. Thecore progress learning progression is a map of skills created, where newlearning is built on previous, foundational understanding of thesubject. A core progress learning progression for a subject is definedin terms of a number of skills. Each skill is represented by a separatedata point. The difficulty value may be derived from the calibrateddifficulty of the test items from standard or existing tests to assessthe skill level. There are several assessment items per skill, called anitem-set.

Common to these perspectives is the idea that the development oflearning progressions is an iterative process. It begins with ahypothesis, informed by what is known about student learning, whichundergoes empirical testing and subsequent refinement based on the data.As another example, a core progress learning progression for reading wasdeveloped according to this iterative model. To reflect the organizationof the standards, a core progress reading learning progression may havefour domains, including 1) foundational skills, 2) language, 3)literature, and 4) informational text. The learning progression iscomprised of five (sub) domains: 1) word knowledge and skills; 2)comprehension strategies and constructing meaning; 3) analyzing literarytext; 4) understanding author's craft; and 5) analyzing argument andevaluating text. For each student group, grade-level domain expectationsmay be identified to describe the desired level of student understandingby the end of the year. These expectations form the foundation of thelearning progression. The learning progression then goes a step furtherto identify the intermediate skills and concepts necessary for studentsto move toward those expectations. Learning progressions are aprogression of cognitive states that move from simple to complex and,while not necessarily linear, the progression is not random, but ratheris sequenced and ordered as “expected tendencies” or “likelyprobabilities” of how learning develops. Inherent in these views ofprogressions is the idea of a coherent and continuous pathway alongwhich students move incrementally through states of increasingcompetence in a domain. Every incremental state builds on and integratesthe previous one as students accrue new levels of expertise with eachsuccessive step in the progression. It is important to note, however,that while progressions may provide clear descriptions of how learningdevelops in a domain, they are not developmentally inevitable. Rather,they are dependent on good curriculum and instruction. The skill areasrepresent the various skills and understandings that students gain asthey progress in their reading development. For example, the grade-levelskill statements identify the incremental steps students take as theyprogress in acquiring specific skills and understandings. It should berecognized that the grade-level skill statements provide specificexamples of relevant words and texts, but do not specify reading contentor identify the activities students should be able to perform to reflectattainment of a skill. They are intended as statements of the skillitself, which serve to advance subject (e.g., reading or math)competence. The skill statements reflect levels of relative difficultyof skills and understandings identified in the progression from theirmost basic, foundational states through increasingly sophisticatedstates of competency. For example, in the learning progression for astudent in grade two, a domain defined for comprehension strategies andconstructing meaning may require a skill (defined in a particular area)identifying the author's purpose, based on an understanding that authorswrite texts for different purposes. Having established this basicunderstanding, students may move incrementally through successive stepsof increasing competence so that by the middle-level grades they areable to evaluate the appropriateness of the form chosen by the author inlight of the author's purpose. These focus skills and prerequisites actas building blocks; each representing a specific level of competency ofa skill or understanding that rests on prior development and that alsoprovides a foundation for the next level of learning. The learningprogression engine 236 identifies for each focus skill, the associatedprerequisites necessary to understand that skill, and provides thesecriteria across grades, skill areas, and domains. To continue with theexample for reading, by the 10^(th) grade, the focus skill may requireanalyzing the cumulative impact of figurative language on wider themesand meanings of the text, from the domain defining an understanding ofthe author's craft. This domain may have five prerequisite skills thatspan two grades and three domains. The learning progress engine 236 maybe further adapted to perform a quantitative analysis to determine whereskills fall on an assessment scale (e.g., standard ones used byeducators). This analysis may compare empirically observed order ofskills (i.e., where skill difficulty falls on a measurement scale) tothe pedagogically determined order of skills (i.e., the most productiveorder of skills for learning a particular skill).

Information and data flows from the Assessment Platform 220, to theexpected-score engine 244, and from that point to the pacing-guidermanager 246. Based on the assessment results (e.g. old or previous) fora particular student or group, the expected-score engine 244 designatesan expected score for that student or group of students. Based on theexpected score for a student, the pacing-guide manager 246 determines apace appropriate for the student or group of students, and theskills-selection engine 248 matches the skills required for the pacedetermined for the student and student group. The recommendation engine250 discovers and finds resources from the resource-finder engine 252.The lesson-organizer engine 254 organizes the lessons for teacher touse. In some embodiments, a teacher may provide input at any stage ofthe planning process, for example, either to the resource-finder engine252, or to other sections or portions of the planning platform 222, inother instances (as indicated by the arrows (e.g. to theskills-selection engine 248). The lesson-organizer engine 254 mayprovide information and data to assessment platform 220 or theassignment platform 226.

The learning-progression engine 236 may be adapted to provide input tothe assessment platform 220, the planning platform 222, oralternatively, to the assignment platform 226, or the reporting platform232.

The grading-framework 262 is adapted to receive information from themastery-maker engine 238 and to the MIRT engine 240. The GradingFramework 4e is also adapted to provide information and data to theAssignment Manager 4d.

The mastery-maker engine 238 is software including routines forproviding information and data to the dashboard services 333 of thereporting platform 232. The mastery-maker engine 238 prescribes practicetests (FIG. 14, 1438 ) and assignments in a particular subject for atarget student to assist the target student with mastering a particularsubject. Some standards for mastery measurement may be used to trackeither long-term progress or short-term progress. In some instances, themastery-maker engine 238 may use general outcome measures (e.g. SAT, ACTetc.) to assess high-level skills (e.g., reading, math, or preparednessfor college) or skill mastery measurement that measures more granularsub-skills (e.g. fluent recall of division involving single digitnumbers with 8 and 9 as divisors). The mastery-maker engine 238 may beadapted to define clear pass/fail criteria, present a multipleequivalent valid forms that measure the same sub-skill, an ability tomeasure improvement even if the mastery criteria is not met, a validunderlying skill sequence, and an opportunity to test whether masteredskills are retained at a later date. The mastery-maker engine 238 insome embodiments is adapted to test depth of knowledge. Themastery-maker engine 238 tests a scale of cognitive demand and alignsassessments with standards. For example, Webb's four levels of cognitivecomplexity include recall and reproduction (level 1), skills andconcepts (level 2), strategic thinking (level 3), and extended thinking(level 4). In some embodiments, mastery may be computed by a combinationof assessments, instruction, and practice inputs. Assignment forms thatcontribute to mastery may include practice (contributing to probedconsideration), formative assessment (contributing to probedconsideration), instruction (contributing to probed mastery), summative(imported data contributing to assessed mastery), and CAT assessment(contributing to assessed mastery). In some embodiments, there are twotiers to probed mastery, including a system tier and an item tier. Insome instances, the system tier may include the requisite items, forms,skills sequences, and mastery criteria. The items may include itemsworked for sub-skills and third-party tagged imported data. In somescenarios, an item % attainment by a student may be computed by an itemscore/highest possible score for the item. A probed % masterydesignation for a student may be computed by a weighted mean for allitem % attainments known to the system. The mastery-maker engine 238 insome embodiments may normalize the outcomes form computer-adaptedtesting with scores from practice tests (FIG. 14, 1438 ) to create anintegrated model that reflects mastery by the target student, which maybe compared or positioned within the learning progression data for thetarget student. The mastery-maker engine 238 may extend actual testingdata by intelligent inferencing schemes by deriving relationships ofobjects within the learning progression.

The MIRT engine 240 is software including routines for binding responsesfrom multiple activities (or assignments or results) received fromassessment, instruction, and practice tests into a unified scale, whichcontributes to determining overall mastery. The MIRT engine 240 mayreceive information and data from the mastery-maker 338. Both themastery-maker engine 238 and the MIRT engine 240 provide data flow tothe reporting platform 232, specifically, the alert manager 335. Thedashboard services 333 and the alert manager 335 provide information anddata to the teacher and the exporter engine exports data out of thereporting platform 337.

FIG. 4 illustrates the various components of the student-growth platform118 coupled by a bus 406 to a communication unit 408, a processor 402, amemory 404, and a data store 410. The integrated student-growth platform118 includes the assessment platform 220, the planning platform 222,learning-progression services 224, the assignment platform 226, themaster-maker engine 228, the MIRT engine 230, and reporting platform232.

The processor 202 processes data signals and program instructionsreceived from the memory 204 and the data storage 210. The processor 202may comprise an arithmetic logic unit, a microprocessor, a general orspecial purpose controller or some other processor array to performcomputations and provide electronic display signals to a display device(e.g., on a user device 106 a). The processor 202 is coupled to the bus206 for communication with the other components. The processor 202 maycomprise various computing architectures including a complex instructionset computer (CISC) architecture, a reduced instruction set computer(RISC) architecture, or an architecture implementing a combination ofinstruction sets. Although only a single processor is shown in FIG. 4 ,multiple processors may be included. It will be obvious to one skilledin the art that other processors, operating systems, sensors, displays,and physical configurations than those that are illustrated may be usedto perform the operations described in this specification.

The memory 204 may be a non-transitory storage medium. The memory 204stores the instructions and/or data for operating the student growthplatform 118, which may be executed by the processor 202. In oneimplementation, the instructions and/or data stored in the memory 204comprises code for performing any and/or all of the techniques orfunctionalities that are described in this specification. The memory 204may be a dynamic random access memory (DRAM) device, a static randomaccess memory (SRAM) device, flash memory or some other memory deviceknown in the art.

The data storage 210 stores the data and program instructions that maybe executed by the processor 202. In one implementation, the datastorage 210 may store the data of various types of users in the webforum. The data storage 210 may include a variety of non-volatile memorypermanent storage device and media such as a hard disk drive, a floppydisk drive, a CD-ROM device, a DVD-ROM device, a DVD-RAM device, aDVD-RW device, a flash memory device, or some other non-volatile storagedevice known in the art.

The communication unit 208 facilitates the communication between theuser device 106 (in FIG. 1 ) and the student-growth platform 118 overthe network 102 (in FIG. 1 ). For example, a user 114 a, via the userdevice 106 a, may access the student-growth platform 118 to view or readelectronic content and otherwise interact with the student-growthplatform 118 and receive information from the student-growth platform118, via the communication unit 208. The communication unit 208 alsodisplays the content or information either received from or hosted onthe student-growth platform 118 to any of the users 114 a through 114 n.

The communication unit 208 couples the student-growth platform 118 tothe network 102 by the signal line 116 (in FIG. 1 ) and via the bus 206.The communication unit 208 may include network interface modules, whichinclude ports for wired connectivity such as but not limited to USB, SD,or CAT-5, etc. The network interface modules are configured to link theprocessor 202 to the network 102 that may in turn be coupled to otherprocessing systems. The network 102 (FIG. 1 ) may comprise a local areanetwork (LAN), a wide area network (WAN) (e.g., the Internet), and/orany other interconnected data path across which multiple devices maycommunicate. The network interface modules are configured to provideconventional connections to the network 102 using standard networkprotocols such as TCP/IP, HTTP, HTTPS and SMTP as well as any othersthat are understood to those skilled in the art. The network interfacemodules include a transceiver for sending and receiving signals usingWIFI, Bluetooth® or cellular communications for wireless communication.Each of the platforms, modules, and/or engines described above mayinclude software or program instructions configured to perform thefunctionalities described here.

Example Student-Growth Platform 118

The example student-growth platform 118 depicted in FIGS. 4 (and 1A) isprovided by way of example and it should be understood that it may takeother forms and include additional or fewer components without departingfrom the scope of the present disclosure. For example, while not shown,in some implementations, the student-growth platform 118 may includeinput and output devices (e.g., a computer display, a keyboard andmouse, etc.). Additionally, it should be understood that the computerarchitecture depicted in FIG. 4 is applicable to the other entities ofthe system 100 a (FIG. 1A), such as the media-distribution server 115and/or the third-party server 117 with various modifications.

The processor 416 includes an arithmetic logic unit, a microprocessor, ageneral purpose controller, or some other processor array to performcomputations and provide electronic display signals to a display device(not shown). The processor 402 may be coupled to the bus 406 forcommunication with the other components of the student-growth platform118. The processor 416 may process data signals and may have variouscomputing architectures including a complex instruction set computer(CISC) architecture, a reduced instruction set computer (RISC)architecture, or an architecture implementing a combination ofinstruction sets. Although only a single processor 216 is shown in FIG.4 , multiple processors may be included. The processor 402 may becapable of supporting the display of images and the capture andtransmission of images, performance of complex tasks, including varioustypes of feature extraction and sampling, etc. It should be understoodthat the student-growth platform 118 could include various operatingsystems, sensors, displays, additional processors, and other physicalconfigurations.

The memory 404 stores instructions and/or data that may be executed bythe processor 402. The memory 404 is coupled to the bus 406 forcommunication with the processor 402 and the other components of thestudent-growth platform 118. The instructions and/or data may comprisecode for performing any and/or all of the techniques described herein.In particular, the memory 404 includes a non-transitory computer-usable(e.g., readable, writeable, etc.) medium, which can be any apparatus ordevice that can contain, store, communicate, propagate or transportinstructions, data, computer programs, software, code, routines, etc.,for processing by or in connection with the processor 402. Anon-transitory computer-usable storage medium may include any and/or allcomputer-usable storage media. In some implementations, the memory 404may include volatile memory, non-volatile memory, or both. For example,the memory 404 may include a dynamic random access memory (DRAM) device,a static random access memory (SRAM) device, flash memory, a hard diskdrive, a floppy disk drive, a CD ROM device, a DVD ROM device, a DVD RAMdevice, a DVD RW device, a Blue-Ray™ storage device, a flash memorydevice, or any other mass storage device known for storing informationon a more permanent basis. It should be understood that the memory 404may be a single device or may include multiple types of devices andconfigurations.

The communication unit 408 is an interface for sending to and receivingdata from other computing devices. In the depicted embodiment, thecommunication unit 408 is coupled to the network 102 by the signal line116 and coupled to the bus 406. In some embodiments, the communicationunit 408 includes a network interface device (I/F) having ports forwired connectivity. For example, the communication unit 408 includes aCAT-5/6/7 interface, USB interface, or SD interface, etc. Thecommunication unit 408 may also include a transceiver for sending andreceiving signals using Wi-Fi, Bluetooth® or cellular communications forwireless communication. The communication unit 408 can link theprocessor 402 to the network 102 that may in turn be coupled to otherprocessing systems. The communication unit 408 can provide connectionsto the network 102 and to other entities of the system 100 usingstandard communication protocols including, for example, TCP/IP, HTTP,HTTPS, etc.

The student-growth platform 118 includes the assessment platform 220,the planning platform 222, the learning progression services 224, theassignment platform 226, the mastery-maker engine 228, and the MIRTengine 230, and reporting engine 232.

In some embodiments, the student-growth platform 118 and/or theassessment platform 220 are sets of instructions executable by theprocessor 402 to provide their respective functionality. In otherembodiments, the student-growth platform 118 and/or the assessmentplatform 220 are stored in the memory 404 of the student-growth platformand are accessible and executable by the processor 402 to provide theirrespective functionality. In any of these embodiments, thestudent-growth platform 118 and the assessment platform 220 may beadapted for cooperation and communication with the processor 402 andother components of the student-growth platform 118.

Example Observation Engine 221

The observation engine 221 is software including routines forfacilitating student growth based on observational assessments receivedfrom the assessment platform 220. In particular, the observation engine221 may send, receive and store observation-related data, such asobservation data, templates and files including questions and answerstied to performance standards (e.g., standards related to execution,compliance, effectiveness, personalized learning plans, etc.), identifyand suggest electronic learning resources (in cooperation with theresource-finder 252) based on observation-related data received,generate reports including analytics and diagnostics about the studentsand their learning progress, generate performance (e.g., execution,evaluation, compliance, effectiveness, etc.) assessments of the studentsbased on demographics data, observation-related data, achievement data,standards data, student data, teacher-oversight data, interaction data,inter-rater reliability data, observer comparison data, or any otherdata described herein.

In the illustrated embodiment, the observation engine 221 cooperateswith the planning platform 222 including the recommendation engine 250,an assignment engine 208, and a reporting platform 232. The observationengine 221 is coupled for communication with the other components of thestudent-growth platform 118. The observation engine 221 is also coupledto the network 102 via the communication unit 408 for communication withthe other entities of the system 100 a (and 100 b).

In some embodiments, the user-interface 119, the observation engine 221,the assessment platform 220, the planning platform 222, thelearning-progression platform 224, the assignment platform 226, themastery-maker platform 228, the multi-dimensional response platform 230,and the reporting platform 232 are sets of instructions executable bythe processor 402 to provide their respective functionality. In otherembodiments, the user-interface 119, the observation engine 221, theassessment platform 220, the planning platform 222, thelearning-progression platform 224, the assignment platform 226, themastery-maker platform 228, the multi-dimensional response platform 230,and the reporting platform 232 are stored in the memory 404 of thestudent-growth platform 118 and are accessible and executable by theprocessor 408 to provide their respective functionality. In any of theseembodiments, the user-interface 119, the observation engine 221, theassessment platform 220, the planning platform 222, thelearning-progression platform 224, the assignment platform 226, themastery-maker platform 228, the multi-dimensional response platform 230,and the reporting platform 232 may be adapted for cooperation andcommunication with the processor 402 and other components 408, 404, and410 of the student-growth platform 118.

The observation engine 221 is software including routines for sending,receiving, processing, and storing observation-related data. In someembodiments, the observation engine 221 may provide observationtemplates to observers for use in observing and assessing other users(e.g., students, also referred to as the targets), receive observationfiles including observation data reflecting the assessments forparticular students, and store the observation files in the data store113 a (FIGS. 1A & 1B) in association with the targets being observed. Insome embodiments, the observation engine 221 interacts and cooperateswith the user/client application 108 a (FIG. 5 ) to provide theabove-noted functionality.

In the illustrated embodiment, the observation engine 221 is coupled toone or more user/client devices 106 (FIGS. 1A & 5 ) to provide one ormore observation templates (FIG. 14 ) to the user/client devices 106 andto receive observation-related data from the user/client devices 106. Insome embodiments, an observation template is an electronic form forassessing the performance of a target student (e.g., generated by thefixed-form engine 205 in FIG. 2A). The observation template may includedifferent header fields for describing the circumstances of anobservation session. For example, the observation template may includefields for describing the identity of a target student, the date theobservation was performed by an observer (e.g. teacher oradministrator), and how the results of the observation should bedistributed (e.g., by reports) and stored (e.g., for later use), etc.Additionally or alternatively, the observation template may includeassessment fields for describing the performance (e.g., execution,compliance, effectiveness, and/or other qualities) of the target studentduring the observation, data about prior observational assessments ofthe target students, data about other observers, etc. In someembodiments, the assessment fields may include data describingpredefined questions and user-selectable or user-definable answers;fields for user-definable questions and/or answers; comment fields forproviding a description of the target student; rubrics, etc. In these orother embodiments, the assessment fields may state a goal, objective(e.g., for mastery), effectiveness expectation (e.g., projections basedon scores), or other metric, and include one or more indicatorsassessing how the target student is meeting that goal, objective,effectiveness expectation, or other metric. For example, the objectivemight be “students develop to meet the vision, mission, values, beliefsand goals of the organization (e.g. school), collaboratively determiningthe processes used to establish these attributes, and facilitating theirintegration into the life of the organization community,” and theselectable indicators assessing whether the student is partiallyproficient at meeting this goal may state that the vision, mission andvalues are: “developed through collaborative process,” “publicallyavailable,” part of routine,” and “routinely updated” by the targetstudent (i.e., from a particular grade). In this example, if only someof these indicators are met, then the target student is deemed partiallyproficient at the goal. If all are met, additional indicators evaluatingwhether a target subject is proficient (as attained a high level beyondthat expected), accomplished, or exemplary at meeting this goal areconsidered and selected if appropriate. The observation templates mayalso include assignment fields for recommending, assigning and/orintegrating electronic resources (e.g., video) by a teacher; and fieldsfor defining assignment parameters for the electronic resources (e.g.,task timers, wait times, etc.), as described in further detail below. Insome embodiments, suggestions for the assignment fields may be populatedin real-time by the assignment platform 226 (particularly, theassignment manager 260) in response to sending the observation data.

The content of the observation templates may be displayed to users viauser interfaces generated (FIG. 14 ) and displayed by the user/clientapplication 108. The user interfaces displaying the content of anobservation template to a user (e.g., student, teacher, oradministrator) may also provide functionality for completing the variousfields of the template. For example, while observing a target subject inthe field, an observer or user 114 may interact with interface elementspresented by the user/client application 108 to input information aboutthe circumstances of the observation and the target's performance. Forexample, the observer or user 114 may input the location where theobservation session took place; the date and time of the observationsession; the identity of the target student's audience (if any);information about the identity of the observer (e.g. teacher oradministrator); information about the observer's position and/orrelationship to the target student (e.g., subject teacher); options forstoring and distributing the results of the observation; etc. Theobserver or user 114 may also provide input describing the performanceof the target student (e.g., teacher comments), such as inputtinganswers to questions about various aspects of the target student'sperformance, etc.

In some embodiments, an observation template may include predefinedquestions and answers for assessing the compliance of a target studentwith various predetermined requirements. For example, the requirementsmay be based on institutional policy, compliance with requirements,legislated practices, or industry standards, and the questions may bedirected to whether or not a target student is meeting thoserequirements/standards. In these embodiments, the same template may beused repeatedly by an observer to record his/her observations of atarget student over time or of a number of different target subjects. Inother embodiments, various different templates may be used for theobservational assessments of a target student. The structure and contentof the observation templates, or portions thereof, may be user-definedor may be automatically generated by the observation engine 221 usingstandards data stored in the data store 113 a or received from anotherentity of the system 100 a, such as the third-party server 117.

The user/client application 108 may transmit observation-related dataincluding input provided by the observer (e.g., teacher oradministrator) during the assessment of the target student to theobservation engine 221 for storage. For example, the observer (e.g.,teacher or administrator) may instruct the client application 108 tosave a completed observation template as an observation file in a localrepository, and then transmit it to the observation engine 221 via thenetwork or cloud platform 102 for storage in the data store 113 a. Theobservation file includes the information from the template upon whichit is based along with the observations (e.g., evaluations, ratings,compliance assessments, and comments), assignments, and/or otherinformation input by observer (e.g., teacher or administrator) duringthe observation.

In the illustrated embodiment, the observation engine 221 is coupled viathe bus 116 (through the network 102 and bus 121 a) to the data store113 a to store and retrieve observation-related data. For example, theobservation engine 221 can store and retrieve the observation templatesand the observation files received from the user/client application 108.The observation engine 221 can also store, retrieve, and provideorganization information associated with observers and target subjects.For example, in the educational setting, the observation engine 221 mayaccess information associated with the organization of the schooldistricts of a state or region; a school district; the schools of aschool district; the teachers and administrators of a school district, aschool, a subject, etc.; the classes in a district or school; thestudents of a school district, a school, a class, a subject, a teacher,an administrator, etc., from the data store 113 a.

The assessment platform 220 is software including routines for providingthe assessments as described above with reference to FIG. 3 . Theplanning platform 222 is software including routines for planning alesson for a teacher according to the assessments. As illustrated inFIG. 3 , the planning platform 222 has the recommendation engine 250,which is software including routines for receiving observation datarelated to a target student, identifying one or more electronicresources that correspond to the observation data, and for providingdata representing the one or more electronic resources for display. Insome embodiments, the recommendation engine 250 is coupled via thenetwork or cloud platform 102 to receive observation data from one ormore user/client devices 106. The observation data may characterize oneor more aspects of a target student's performance during an observationsession performed by an observer (e.g. teacher or administrator). In theillustrated embodiment, the recommendation engine 250 is coupled to thedata store 113 a via the bus 116 (and 121 a) to store and retrieve data,and is coupled to the media data store 111 via signal line 127 and thenetwork 102 to store and retrieve data.

In some embodiments, the observation data may accompany a resourcerequest for a list of electronic resources that correspond to theobservation data. The recommendation engine 250 may receive the requestfrom a client device 106, and may satisfy the request by identifying oneor more electronic resources that correspond to the request, and providea resource response including a summary of the one or more resources tothe user/client device 106 for display to the user 114 of the clientdevice 106. For example, an observer of a target student may provideinput reflecting observation data assessing the performance of thetarget subject, and the client application 108, upon receiving thatinput, may transmit a request for recommended electronic instructionalresources that can be assigned by the observer to the target student tohelp the target student improve his or her skills in a given area.

In some embodiments, to identify one or more electronic resources thatcorrespond to the observation data accompanying the resource request,the recommendation engine 250 can compare the observation data tometadata associated with electronic resources to identify resources thatmatch the observation data. For example, the recommendation engine 250can search a resource library database that includes an index or catalogof the electronic resources that are available. For instance, theresource library database can include metadata for each of theelectronic resources describing each resource. The metadata can includetags describing various characteristics of an electronic resource, agraphical image of the resource (e.g., a thumbnail), a description ofthe topic or subject matter that the resources is directed to, an authoror authors of the resource, the publisher of the resource, thepopularity of the resource including, for example, the number of userswho have consumed the resource and the level of their interactivity withthe resource, etc. The recommendation engine 250 can query the resourcelibrary database using the observation data or aspects thereof toidentify resources that have corresponding metadata that match theobservation data, either loosely or strictly.

The electronic resources may be distributed among several data storeslocated across the network or cloud platform 102 or may be stored in asingle data store. In the illustrated embodiment, the media store 111and the data store 113 a work cooperatively to store the electronicresources. For example, media objects such as video, audio, e-books,vector-based files, documents, datasets, learning objects, etc., may bestored in the media store 111 and lesson plans, learning progressions,curriculum maps, publications, portfolios, industry standards, etc., maybe stored in the data store 113 a. In other embodiments, all of theelectronic resources may be stored in and accessible from a singleinformation source, such as the media store 111, the data store 113 a-n,etc. In any of the foregoing embodiments, the resources stored in thedata store may be cataloged, for example, by the recommendation engine250, in a single resource library database or in resource librarydatabases distributed over the network 102, and the recommendationengine 250 can query the resource library database or resource librarydatabases for information matching various criteria or for informationabout the resources. In other embodiments, the electronic resources maybe prescribed or predetermined in advance and pushed out by thestudent-growth platform 118 to the observer of a target student forassignment or to the target student directly for consumption.

In some embodiments, the observation data includes data quantifying anobserver's assessment of a target student's performance. For example,the observation data may include an answer input by an observer inresponse to a question about the target student's performance in aparticular area, and the answer may quantify how well a target subjectis performing. In some embodiments, the answers to questions may bebased on predefined performance scales that are defined to therecommendation engine 250 and the recommendation engine 250 may use theanswer to determine where the target student lies within thatperformance scale. For example, a target student's performance in aparticular area may be assessed from worst to best using the followingidentifiers: “unsatisfactory,” “needs improvement,” “developing,”“proficient,” and “distinguished,” or other such method for scaling astudent and if the observation data includes data identifying“unsatisfactory” as the answer to a particular question about a targetstudent's performance in that area, the recommendation engine 250 mayuse this assessment to identify one or more electronic resources thatprovide foundational or basic learning in that particular subject area.

If multiple electronic resources are identified by the recommendationengine 250 as corresponding to the observation data, the recommendationengine 250 can rank them based on one or more criteria. A criterion maybe any attribute associated with the electronic resources. For example,the criterion may include a topic; the number of times an electronicresource has been interacted with, viewed, listened to, etc.; an author;a publisher; a date of the electronic resource; the number of usersconnected (or at the same level) to the target student who haveinteracted with the electronic resource previously; the number of timesan electronic resource has been assigned to users having a similarassessment; etc. The recommendation engine 250 can generate the summaryof electronic resources based on the ranking performed by it. Forexample, the top-ranked electronic resource may be listed first in thesummary and the lowest-ranked resource may be listed last. In anotherexample, the recommendation engine 250 may limit the summary to acertain number of top-ranked resources. In yet another example, the listof electronic resources may be sorted in order of rank and providedincrementally as needed by the user application 108. In a furtherexample, the recommendation engine 250 may rank the resources by thosewho have been most impactful/effective for students similar to thetarget student. For example, the recommendation engine 250 may usedemographics, observation, achievement, interaction, standards, student,and/or teacher data, etc. to identify the resources that were the mosteffective at helping a set of similar target subjects developprofessionally. For example, a target student may be a fourth grader whois struggling with maintaining a level appropriate for the grade. Therecommendation engine 250, using demographic data and/or profile data,may identify other fourth graders who, based on their respectiveobservation data and/or achievement data, also initially struggled withmaintaining the level and who later became proficient at that level, asreflected by their respective observation data and/or achievement data,by watching a learning video(s) on particular subject areas (e.g.,math); and the recommendation engine 250 and may recommend this/thesevideos for assignment/consumption.

The learning-progression platform 224 is software for placing thestudent in a learning-progression scheme and for following thelearning-progression scheme prescribed for a target student. Theassignment platform 226 is software including routines for receiving anassignment request requesting an assignment of one or more electronicresources to the target student for completion, and for assigning theone or more electronic resources to the target student based at least inpart on the assignment request. In some embodiments, the assignmentplatform 226 is coupled via the network 102 to receive the assignmentrequest from one or more client devices 106.

The assignment platform 226 may interact with the user/clientapplication 108 to assign various electronic resources to a targetstudent. For example, during an observation of the target student, theobserver inputs observational data indicating that the target student isin need of training on a particular skillset, and the recommendationengine 250 provides a summary of electronic instructional/trainingresources that are accessible via the student-growth platform 118. Theobserver, using an interface rendered and displayed by the user/clientapplication 108, may assign one or more of the electronic resources tothe target student. In response to the assignment, the assignment unit518 (FIG. 5 ) of the user application 108 generates and sends andassignment request to the assignment platform 226, which identifies theelectronic resource or resources that have been assigned, as furtherdiscussed below with reference to at least FIG. 3 . The assignmentplatform 226 then records the assignment of the electronic resources inthe data store 113 in association with a user profile for the targetstudent. In some embodiments, an assignment is not activated by theassignment platform 226 until the corresponding observation fileincluding the assignment is finalized and uploaded by the observationunit 516 (FIG. 5 ) of the user/client application 108. In otherembodiments, one or more assignment requests are provided and recordedby virtue of the observation file being uploaded for storage by theuser/client application 108 to the student-growth platform 118. Forexample, upon receipt of the observation file, the assignment platform226 extracts any assignments from the observation file and records themas described above. In some embodiments, to complete the assignment, thetarget student, who is a user of the student-growth platform, may berequired to access the service and interact with the electronicresource. In other embodiments, to complete the assignment, the targetstudent may be required to consume the electronic resource and thenreport on his/her implementation of the learning provided by theresource and/or provide his/her reflections on the learning provided bythe resource, etc., via the user/client application 108. For example,the target student may be required to submit, via the user/clientapplication 108, input describing his/her experience withtrying-out/implementing the principles taught by the assigned resource(e.g., an online learning video). Once this input has been received, theassignment platform 226 may flag the assignment as being completed inthe data store 113. Other configurations for completing an assignmentare also contemplated.

In some embodiments, the assignment request includes one or moreassignment parameters or particulars. Each assignment parameter sets acondition that must be met in order to complete the assignment. Forexample, an assignment parameter includes a due date, a level ofinteraction with the electronic resource that is required to completethe assignment, an additional requirement that must be satisfied forcompletion of the assignment, etc. For instance, the observer may assigna video to the target student to view and may require the target studentto write his/her thoughts or reflections about the video by inputtingand transmitting them via an interface associated with thestudent-growth. In the illustrated embodiment, the assignment platform226 is coupled to the data store 113 a-n via the bus 116 to store theone or more assignment parameters in association with assignment towhich they pertain. In these or other embodiments, one or moreassignment parameters can be predefined and stored in the data store 113a-n. A predefined assignment parameter can be applicable to all userswho are assigned electronic resources, or may be customized for aparticular group of users, such as those belonging to a particularschool or grade or being observed by a particular observer (e.g.,teacher). For example, for all videos that are assigned, a predefinedassignment parameter can be set (e.g., by an observer via an associatedinterface of the student-growth platform 118) requiring that the videosmust be viewed to completion in order for the assignments of thosevideos to be considered satisfied. In another example, predefinedassignment parameters can require videos to be viewed to completion infull screen mode with the sound of the video being set at an audiblelevel in order for the assignments for the videos to be consideredsatisfied.

In some embodiments, the assignment engine 226 generates and sends anelectronic notification to the users associated with the assignmentrequest. For example, the assignment engine 226 may send an email to thetarget subject and/or the observer(s) summarizing the assignment. Theemail may include a description of the electronic resource and anelectronic link (e.g., a hyperlink including the uniform resourcelocator (URL) of the electronic resource) for directing the readerdirectly to the electronic resource. The email may also describe anyassignment parameters, such as when the assignment must be completed by.In another example, the assignment platform 226 may send a similarmessage to the user via an internal messaging system, aninstant-messaging system, a text-messaging system, or any otherelectronic-messaging system. In these embodiments, the assignmentplatform 226 is coupled to the data store 113 a-n to access informationabout the electronic resource and to store a copy of the electronicnotification that was sent.

The mastery-maker platform 228 is software including routines forenabling mastery of a particular subject. The details are describedabove with respect to FIG. 3 . The multi-dimensional response platform230 is software including routines for binding various responses.

The reporting platform 232 is software including routines for generatingand sending reports. The reporting platform 232 may use the datastored/and or aggregated by the student-growth platform such asachievement data, demographics data, student data, teacher data,observation-related data, interaction data, standards data, or any otherdata described herein, to generate the reports. For example, thereporting platform 232, using the data aggregated and stored by theobservation engine 221 and/or student-growth platform 118, maygenerate/segment/organize a report by region, district, school, class,teacher, student(s), class-size, gender, ethnicity, public policy,legislation, standards, requirements, etc. In a further example, thereporting platform 232 may process this data to make macro and/or microqualitative assessments for inclusion in one or more reports. Forinstance, the reporting platform 232, based on the observation-relateddata, demographics data, achievement data, student data, teacher data,interaction data, and/or standards data, etc., may generate an aggregateeffectiveness score for a region, body, or group, and/or individualeffectiveness scores for each of the students/teachers of that region,body, or group. The reports may be generated by the reporting platform232 to include any type of data including textual, graphical, video,audio, and vector-based data to provide rich, qualitative andquantitative analysis of the target subject(s), observer(s), andassociated organization(s) or businesses(s), including their performance(e.g., execution, effectiveness, compliance, problem-areas, etc.).

In some embodiments, the reporting platform 232 may analyze two or moredata types, such as observation-related data, achievement data, and/orstudent data related to the target subject, to generate an effectivenessrating for that target subject. Analyzing two more data types togenerate an effectiveness rating is advantageous as it can provide amore reliable effectiveness rating for a target subject compared to aneffectiveness rating generated from a single data type. For instance,the observation data for a given teacher may reflect, for a particularevaluation period, that the teacher received a rating of “proficient”for four of the metrics evaluated and a “needs improvement” rating forthree of the metrics. However, during this same evaluation period, thestudent data may reflect that the students of this teacher gave theteacher a “proficient” or “excellent” rating in every category surveyed,and the achievement data for these students may reflect standardizedtest scores, which meet or exceed legislative requirements. As a result,the effectiveness rating generated by the reporting module 210 canbalance the “needs improvement” ratings against the positive survey andtest score results to produce a more accurate overall “effectiveness”rating for the teacher. In other examples, the reporting platform 232may determine the assessments of the target subject described by eachdata type as being consistent, and as providing further evidence/supportfor a particular effectiveness rating.

In some embodiments, the reporting platform can generate a report basedat least in part on the receipt of interaction data describing aninteraction between the target subject and the at least one electronicresource that was assigned. The reporting platform 232 may be coupled tothe resource-finer engine 252 (FIG. 3 ), the memory 404, and/or the datastore 113 a-n to receive the interaction data. For example, to generatea report, the reporting platform 230 may analyze user behavior ininteracting with one or more electronic resources provided by theresource-finder engine 252, and generate a report summarizing and/ordetailing this analysis. In particular, when a user consumes anelectronic resource, the resource-finder engine 252 of thestudent-growth platform 118 may receive and store interaction datadescribing the interaction in the data store 113 a-n in association witha user profile associated of the user, and the reporting platform 232may access the interaction data to analyze the user interaction andresults and generate a report describing the user interaction andresults.

For example, when a user accesses an electronic resource, pages throughan electronic book, downloads files included with or embedded in awebpage, complete a survey associated with any electronic resource,views a video file, listens to an audio file, comments on passages of aninteractive electronic book, submits lesson plans, submits curriculummaps, downloads documents, uploads files including video, audio, text,graphics, etc., participates in communities, groups defined by his/hersocial connections, or otherwise uses any other functionality providedby the user/client application 108 (e.g., see FIG. 5 ) to interact withan electronic resource. The student-growth platform 118 the receivesinteraction data describing these interactions from the user/clientapplication 108 or another entity of the system, such as themedia-distribution server 117, and stores interaction data describingthe interaction in the data store 113 a-n. In another example, if anobserver assigns a target student the task of watching a video onachieving effective scores via the student-growth platform 118, thereporting platform 232 can generate status updates about the targetstudent's progress on watching the video and sending them to theobserver (e.g. teacher). The reporting platform 232 can also report onthe target student's additional efforts to develop his/her skills byreporting on what other electronic learning resources the target studenthas consumed since the observer made the assignment, provided the targetstudent provides his/her consent for doing so via an associated privacysettings interface.

In some embodiments, the reporting platform 232 generates a report inresponse to receiving a trigger signal. In some embodiments, the triggersignal may be generated by the student-growth platform 118 upon thecompletion of an assignment by a target user and transmitted to thereporting module 232. In other embodiments, the trigger signal may begenerated in response to a request for a report, for example, from auser of the student-growth platform via an associated user interface.For example, an observer who observed a target student and assigned thetarget student one or more electronic resources may input a command intohis/her user device 106 via the user application 108 commanding that areport be generated describing the target student's progress oncompleting the assignment. Responsive to receiving the command, the userapplication 108 may generate and send a report request via the network102 to the reporting platform 232, thus triggering the reportingplatform 232 to generate and send the report for display to the targetstudent, observer, an administrator, a combination of the foregoing,etc.

In other embodiments, the reporting platform 232 may automaticallygenerate the report at certain intervals, times, etc. For example, thereporting platform 232 may automatically generate reports for alloutstanding assignments and send them to the administrator and/orobserver users 114 who oversee the target students that the outstandingassignments correspond to. In some embodiments, the reporting platform232 may transmit the report to the user application 108 for display tothe user 114, provide the report for download as a portable document,transmit the report via electronic message (e.g., via email) to one ormore other users 114 associated with or responsible for the targetsubject, etc.

The reporting module 232 is also capable of analyzing theperformance/effectiveness of an observer/student, and generating andproviding a report describing the observer's/student'seffectiveness/performance to the observer and other users 114, such asan administrator of the observer. In some embodiments, to analyze theeffectiveness/performance of the observer/student, the reportingplatform 232 compares achievement data and observation-related dataassociated with the target to determine if the performance assessment ofthe target reflected by the observation-related is accurate andconsistent. The achievement data can include any type of achievementdata associated with the target. For example, depending on the targetstudent's performance, the achievement data may include test scores forthe target, reviews by teachers, performance reviews, compliance withrequirements/standards, etc. The observation data can include any dataassociated with the performance assessments made by an observer, such asthe observation files associated with the observer and/or targetstudents observed by the observer. In these or other embodiments, thereporting platform 232 can track the observational assessments performedfor the target student and compare them for consistency based onsubstance, frequency, etc.

Based on the observation-related and achievement data, the reportingmodule 232 can determine the accuracy and consistency of a performanceassessment (e.g., execution, effectiveness, compliance, performance,trending, and other metrics, etc.) of the target students. In someembodiments, the reporting module 232 can analyze the achievement datato determine an achievement-based performance assessment for the targetstudent; can analyze the observation-related to determine anobservation-based performance assessment for the target student; andcompare the achievement-based and the observation-based performanceassessments to further determine if the observation-based performanceassessment of the target student is accurate/consistent. In otherembodiments, the reporting platform 232 may compare the observationalassessments by one observer of a target student to the observationalassessments of the same target student by other previous observers todetermine the accuracy of the observer's assessments. For example, if anobservational assessment of a target student by a first observer isgrossly inconsistent with the observational assessments of that targetstudent by other observers on the same or similar subject matter, theobservational assessment of the first observer may be flagged andreported to an administrator of the observer for furtherreview/scrutiny.

In some embodiments, the accuracy of the observation-based performanceassessment can be determined based on whether the achievement-based andthe observation-based performance assessments are consistent. Forexample, the reporting platform 232 may determine the observation-basedperformance assessment to be inaccurate if the observation-basedperformance assessment is negative and the achievement-based performanceassessment is positive, or conversely, if the observation-basedperformance assessment is positive and the achievement-based performanceassessment is negative.

Further, the reporting platform 232 may determine the observation-basedperformance assessment to be accurate if both the observation-basedperformance and achievement-based performance assessments were negativeor positive. However, if the both the observation-based performance andthe achievement-based performance assessments were neutral, thereporting platform 232 may report that the accuracy of the performanceassessment made the by the observer could not be verified.

The reporting platform 232 can generate a report describing thedetermination it made about the accuracy of the observer's performanceassessment of a target subject and provide the report for display to theobserver(s) or one or more other users, such as an administrator of theobserver(s). In some embodiments, the reporting platform 232 cangenerate the report in response to receiving a request from a clientdevice 106 of an administrator/user 114 who oversees the observer. Inother embodiments, the reporting platform 232 can automatically generateand send the report to the administrator via an electronic message, suchas an email, an internal messaging application provided by the studentdevelopment application, a text message, etc.

In some embodiments, the accuracy of all of the observer's performanceassessments of a particular target student or multiple target studentsmay be determined by the reporting platform 232 and included in thereport. For example, the observer's overall accuracy in performing theobservational assessments may be computed over time by the reportingplatform 232 to determine if the observer is consistently inaccuratewith his/her observations. Additionally, the reporting platform 232 maycompare the accuracy of one or more of an observer's assessments of atarget student to the assessments of that target student by otherobservers to determine whether they are consistent. If not, informationdescribing the inconsistencies may be included in the report.

The reporting platform 232 may also determine whether an observer isproperly performing the observational assessments and can include thisdetermination in the report. In some embodiments, the reporting platform232 may analyze the observation files for some or all target studentsobserved by the observer to determine the level and quality of feedbackprovided by the observer about those students. For example, if thereporting platform 232 determines that the assessments (e.g., answers,ratings, comments, etc.) for the target students made by the observer inthe observation files are all the same or substantially similar, thereporting platform 232 may determine that the observer is simply makingthe same assessments for each target student and is not performing theassessments as required. The reporting platform 232 may also make adetermination as to the quality of one or more assessments performed byan observer based on the level and/or variety of feedback included inthe observation file(s) for one or more target students.

The reporting platform 232 may store any reports and/or data generatedby it in the data store 113 a-n for later access by the reportingplatform 232 or any other component of the student-growth platform 118,such as an administrative module (not shown) of the student-growthplatform 118 that provides administrator/users access via the clientapplication 108 to statistics and reports about the users 114 of thestudent-growth platform 118 that the administrator oversees.

In the depicted embodiment, the reporting platform 232 is coupled to thedata store 113 a-n via the bus 116 via the network/cloud platform 102and the third-party server 117 to receive the achievement data. Forexample, the reporting platform 232 can periodically retrieve theachievement data from the third-party server 117 via an API and store itlocally in the data store 113 a-n for later access or use. In anotherexample, the reporting platform 232 can retrieve the achievement datareal-time via the API for analysis and compare it to theobservation-related data from the observation file. However, in otherembodiments, the reporting platform 232 may retrieve the achievementdata from any information source communicatively coupled to thestudent-growth platform 118 or network 102 via the network.

The reporting platform 232 provides numerous additional advantagesincluding providing the target student a mechanism for reporting on thecompletion of an assignment, providing an observer/user a mechanism tomonitor whether the target student(s) he/she observes completes theassignments assign to them, analyzing and reporting on an student'sperformance and work quality, determining/rating effectiveness of targetstudents, etc.

Additional functionality of the student-growth platform 118 and itsobservation engine 221, and their corresponding components are furtherdescribed below.

Example Client Device 108

FIG. 5 is a block diagram of an example user/client device 106. In thedepicted embodiment, the client device 106 includes a client application108. The client device 106 also includes a communication unit 308, aprocessor 302, a memory 304, a display device 310 with a graphicsadapter 320, a display 318, and an input device 312, which arecommunicatively coupled via the bus 306. In some embodiments, thefunctionality of the bus 306 may be provided by an interconnectingchipset.

The communication unit 308 includes interfaces for interacting withother devices/networks of devices. In some embodiments, thecommunication unit 308 includes transceivers for sending and receivingwireless signals. For example, the communication unit 308 includes radiotransceivers (4G, 3G, 2G, etc.) for mobile network connectivity, andradio transceivers for WiFi and Bluetooth® connectivity. In these orother embodiments, the communication unit 308 may include a networkinterface device (I/F), which includes ports for wired connectivity. Forexample, the communication unit 308 may include a CAT-type interface,USB interface, or SD interface, etc. In the depicted embodiment, thecommunication unit 308 is coupled to the network 105 (FIG. 1 ) by thesignal line 104 a-n.

The processor 302 comprises an arithmetic logic unit, a microprocessor,a general purpose controller, or some other processor array to performcomputations and optionally provide electronic display signals to thedisplay device 310. The processor 302 may communicate with the othercomponents via the bus 306. Processor 302 processes data signals and maycomprise various computing architectures including a complex instructionset computer (CISC) architecture, a reduced instruction set computer(RISC) architecture, or an architecture implementing a combination ofinstruction sets. Although only a single processor is shown in FIG. 5 ,multiple processors may be included. The client device 106 also includesan operating system executable by the processor 302 as discussedelsewhere herein, for example, with reference to FIG. 1 .

The memory 304 stores instructions and/or data that may be executed byprocessor 302. The memory 304 communicates with the other components ofclient device 106 via the bus 308. The instructions and/or data comprisecode for performing any and/or all of the techniques described herein.In particular, the memory 304 includes a non-transitory computer-usable(e.g., readable, writeable, etc.) medium, which can be any apparatus ordevice that can contain, store, communicate, propagate or transportinstructions, data, computer programs, software, code, routines, etc.,for processing by or in connection with the processor 302. Anon-transitory computer-usable storage medium may include any and/or allcomputer-usable storage media. In some implementations, the memory 304may include volatile memory, non-volatile memory, or both. For example,the memory 304 may include a dynamic random access memory (DRAM) device,a static random access memory (SRAM) device, flash memory, a hard diskdrive, a floppy disk drive, a CD ROM device, a DVD ROM device, a DVD RAMdevice, a DVD RW device, a flash memory device, or any other massstorage device known for storing information on a more permanent basis.It should be understood that the memory 304 may be a single device ormay include multiple types of devices and configurations. In someembodiments, the user/client application 108 is stored in the memory 304and executable by the processor 302.

The display device 310 represents any device equipped to present outputsignals generated and provided by the user/client device 106. In someembodiments, the display device 310 displays electronic images and dataincluding, for example, user interfaces and formatted information. Forexample the display device 310 may be any conventional display device,monitor or screen, such as an organic light-emitting diode (OLED)display, a liquid crystal display (LCD), an e-ink display, etc. In someembodiments, the display device 310 is a touch-screen display capable ofreceiving input from one or more fingers of a user/client 106. Forexample, the display device 310 may be a capacitive touch-screen displaycapable of detecting and interpreting multiple points of contact withthe display surface. In some embodiments, the display device 310 may becoupled to the bus 306 via a graphics adapter 320 (shown within thedisplay device 310, but also may be configured outside), which generatesand provides display signals to the display device 310. The graphicsadapter 320 may be a separate processing device including a separateprocessor and memory (not shown) or may be integrated with the processor302 and memory 304.

The input device 312 represents any device for inputting data on theclient device 106. In some embodiments, the input device 312 is atouch-screen display capable of receiving input from the one or morefingers of the client/user 106. The functionality of the input device312 and the display device 310 may be integrated, and a user/client 106of the client device 106 may interact with the client device 106 bycontacting a surface of the display device 310 using one or morefingers. For example, the user/client 114 a-n may interact with anemulated (i.e., virtual or soft) keyboard displayed on the touch-screendisplay by using fingers to contacting the display device 310 in thekeyboard regions. In other embodiments, the input device 312 is aseparate peripheral device or combination of devices. For example, theinput device 312 includes a keyboard (e.g., a QWERTY keyboard) and apointing device (e.g., a mouse or touchpad). The input device 312 mayalso include a microphone (e.g., for voice input) or other knownperipheral devices.

Example User/Client Application 108

Referring now to FIG. 5 , the user/client application 108 is softwareincluding routines for sending and receiving data to the other entitiesof the system, including, for example, the student-growth platform 118,the media-distribution server 115, and the third-party server 117. Insome embodiments, the user/client application 108 a is a web browserapplication for accessing the resources provided by the student-growthplatform 118 and the media-distribution server 115. For example, thestudent-growth platform 118 operated by the in cooperation with themedia-distribution server 115 may be a web-based service and theuser/client application 108 may access various electronic resourcesprovided by the service via uniform resource locators (URLs). In otherembodiments, the user/client application 108 a is an applicationcustomized specifically for accessing the student-growth platform 118,and more particularly, for cooperating and interacting with theobservation engine 119.

In the depicted embodiment, the user/client application 108 provides auser 114 a-n (e.g., an observer) interacting with the client device 106mechanisms for inputting viewing, adding, modifying, deletingobservation-related data related to one or more other users/clients 114a-n. The user/client application 108 may cooperate with the observationengine 221 (FIG. 1A) to conveniently store and retrieve observationtemplates and files for viewing by the user. The user/client application108 may, in some embodiments, send a resource request to the observationengine 221 to identify and provide recommended electronic resources thatcan be assigned to a user. The user/client application 108 may also senda request to the reporting module 232 (FIG. 1A) to provideobservation-related statistics and reports for display to the user 114a-114 n via a report interface generated by the user-interface module514 of the user/client application 108.

In the illustrated embodiment, the user/client application 108 includesa user-interface module 514, an observation unit 516, and an assignmentunit 518. The observation unit 516, the assignment unit 518, and theuser-interface module 514 are communicatively coupled with each otherand the other components 502, 504, 508, 510, and 512 of the clientdevice 106. The components are also coupled to the network 102 via thecommunication unit 508 (and line 104) for communication with the otherentities of the system 100 a. While not shown, in some embodiments, theuser/client application 108 may include an authentication orverification module for authenticating the user 114 a-n to access thestudent-growth platform 118.

In some embodiments, the user/client application 108, the user-interfacemodule 514, the observation unit 516, and/or the assignment unit 518 aresets of instructions executable by the processor 502 to provide theirrespective functionality. In other embodiments, the user/clientapplication 108, the user-interface module 514, the observation unit516, and/or the assignment unit 518 are stored in the memory 504 of theclient device 106 and are accessible and executable by the processor 502to provide this functionality. In any of these embodiments, theuser/client application 108, the observation unit 516, the assignmentunit 518, and/or the user-interface module 514 may be adapted forcooperation and communication with the processor 502 and othercomponents of the user/client device 106.

In some embodiments, the observation-related data managed by theuser/client application 108 may be locally stored in the memory 504,remotely stored in any of the data stores 113 a-113 n (via signal lines121 a-121 n), the third-party server 117, or may be stored in anycombination of the forgoing thereof. For example, an instance of theobservation-related data may be stored locally on the user/client device106 and remotely on the student-growth platform 118, and the client/userapplication 108 may synchronize the information via the network 105,either continuously or periodically, as the information changes. In someembodiments, the user/client application 108 may be a stand-aloneapplication or may be integrated into another application operable onthe user/client device 106.

The observation unit 516 is software including routines for sending andreceiving observation-related data to the observation engine 221 (FIG.1A), cooperating with the interface engine 306 to displayobservation-related information to a user, and cooperating with theuser-interface unit 119 to receive observation-related input from theuser/client. In some embodiments, the observation unit 516 interactswith the observation engine 221 to receive observation templates andobservation files for display to the user 114 a-n of the user/clientdevice 106 and to send observation files to the observation engine 221for processing and/or storage in the data store 113 a-n, as discussedabove with reference to at least FIG. 1A.

In some embodiments, the observation unit 516 can cooperate with theobservation engine 221 via the network 102 to provide information abouttarget students to an observer and provide functionality to the observerfor assessing and tracking the performance and development of the targetstudents. The observation unit 516 may also interact with theuser-interface module 514 to provide administrative tools such as areporting tool for viewing statistics and other analytical data, and/oran observational tool for assessing the performance of students,assigning instructional resources to students, and tracking completionof the assignments given to them. In some embodiments, the observationunit 516 interacts with the user-interface module 514 to displayobservation templates and files to a particular user, as discussed withreference to at least FIG. 14 below.

The observation unit 516 may be coupled to the user-interface module 314to receive user input and display the information to the user 1114 a-114n via user interfaces generated by the user-interface module 514, suchas the observation interface discussed with reference to FIG. 14 below.For example, the observation unit 514 may send interface signals to theuser-interface module 314, and responsive to receiving these signals,the user-interface module 314 may generate and display user interfacesthat correspond to the instructions carried by the interface signals. Inanother example, the user-interface module 314 may receive input signalsfrom a user via the input device 312 and send those signals to theobservation unit 314 for processing. In some embodiments, in cooperationwith the user-interface module 314, the observation unit 314 can receiveuser-related and observation-related information and display the data tothe user, display observation templates to the user, populateobservation templates with user input, save observation files based onthe observation templates, transmit observation-related data such asobservation files to the observation engine 221 or storage, receiveobservation-related statistics and reports and organize and display themto the user, receive electronic resources for assignment, consumption,etc., by the user, receive electronic communications from other usersvia the network 102 and display them to the user, etc. In someembodiments, an observer may, via a user interface rendered by theuser-interface module, preselect options and/or be guided similarly indesigning observation templates and appropriate follow-up activities.

In some embodiments, the user-interface module 514, in cooperation withthe observation unit 316, may generate a report dashboard/interface forviewing reports generated and provided by the reporting module 232 (FIG.1A) and received by the observation unit 514. This dashboard providesnumerous advantages including providing an observer or administratorwith detailed information about a given target student's performance(e.g., execution, effectiveness, compliance, etc.) over time. Forexample, the observer may be a teacher and may need to interact with anumber of students to perform observational assessments of each of them.For each student, the teacher may, using the dashboard, access anyprevious observational assessments of that student; view an overallperformance (e.g., execution, effectiveness, compliance, etc.)rating/summary of that student (scores assigned); view the performance(e.g., execution, effectiveness, compliance, etc.) ratings/summaries ofthat student over time; view statistics across all observationalassessments of that student or a subset, such as the observationalassessments performed for that academic year; may quickly ascertain theareas a student has had problems with or has been working on, or theareas the student has been improving on; review the test scores for thestudents, evaluations of the student; view the electronic trainingresources the student has consumed/interacted with; view anywork-product, lesson plans, videos, presentation, etc., the student hasuploaded, the learning communities and groups the student has interactedwith, any mentors the student has been working with, etc. Using thisinformation, the teacher may quickly get up-to-speed on where thestudent is at, thus provide pertinent and relevant observations (e.g.,evaluations, ratings, suggestions, comments, etc.) and assignments,etc., during the observation session to be performed.

The assignment unit 518 is software including routines for generatingand sending resource requests, receiving resource responses includingone or more electronic resources identified by the assignment platform226, and assigning one or more electronics resources to a user. In someembodiments, the assignment unit 518 cooperates and interacts with theassignment platform 226 to identify one or more electronic resourcesthat can be assigned to a user, as discussed above with reference to atleast FIG. 1A.

The assignment unit 518 is coupled to the user-interface module 514 toreceive user input and provide information to the user/client 114 a-nvia user interfaces generated by the user-interface module 514. In someembodiments, responsive to receiving user input signals, the assignmentunit 518 can generate a resource request or an assignment request. Insome embodiments, the input signals may specify which electronicresource(s) is/are being assigned and the user the resource(s) is/arebeing assigned to. For example, an observer performing and observationof a target student, may select one or more of the videos identified bythe recommendation engine 250 (FIG. 2A) and displayed via theuser-interface module 514, such as the observation interface 1400illustrated in FIG. 14 . The assignment unit 518 may also assignsupplemental instructional, prescriptive and/or discipline-relatedresources in response to one or more of these resources being assignedby an observer (e.g., after receiving a report about an initialassignment). In some embodiments, the assignment unit 518 assigns one ormore of these resources by generating and sending an assignment requestand receiving an assignment confirmation as discussed elsewhere herein.In addition, the assignment unit 518 may provide tools/functionality tothe observer to provide the target student with feedback, follow-up withthe target student about an assignment or an aspect observationalassessment performed, provide recommendations of additional electronicresources to assign to the target subject upon completion of an initialassignment by the target student, etc.

The user-interface module 514 is software including routines forrendering user interfaces and for receiving user input. Theuser-interface module 514 may be coupled to the input device 512 via thebus 506 to receive input signals from the user 114 a-n. For example, anobserver/user 114 a-n can select an answer to an observation-relatedquestion using the input device 512, and the user-interface module 514receives signals describing the answer. The user-interface module 514may store the input signals in the memory 504 for retrieval by the otherelements of the client application 508, such as the assignment unit 518,or may provide the signals directly to the other elements of theuser/client application 108.

The user interfaces generated by the user-interface module 108 includeinterfaces for inputting, modifying, and deleting information,displaying notifications, rendering video, displaying images and text,displaying vector-based content, sending and storing information, etc.In some embodiments, the user interfaces include user interface elementsthat allow users/clients 114 a-n to interact with the user/client device106 and input information and commands, such as text entry fields,selection boxes, drop-down menus, buttons, virtual keyboards and numericpads, etc., as further discussed below with reference to FIG. 14 .

Example Methods

Referring now to FIG. 4 , an example method 400 for prescribingelectronic resources based on observational assessments is described.The method 400 begins by identifying 402 one or more electronicresources based on observation data. In some embodiments, therecommendation engine 206 identifies 402 the one or more electronicresources by querying a library of electronic resources for resourcesthat match one or more aspects of the observation data. If a pluralityof electronic resources is identified, the recommendation engine 206 canrank and filter the electronic resources and thus recommend whichelectronic resources are the most suitable for a target subject. Next,the method 400 provides 404 a summary of the one or more electronicresources to an observer, such as a supervisor or evaluator, forassignment to subject that he/she is observing. For example, the clientdevice 126 of the observer may receive a summary of training videos orother resources identified and ranked by the recommendation engine 206and may display the summary to the observer via a user interface. Theobserver may use the interface to preview the videos or other resourcesand/or assign one or more of the videos or other resources to the targetsubject.

Next, the method receives 406 an assignment of one or more electronicresources. In some embodiments, the assignment engine 208 receives anassignment request describing the one or more electronic resources thatare to be assigned to the target subject by the assignment engine 208.The method 400 continues by associating 408 the assignment of the one ormore electronic resources with the target subject. In some embodiments,to associate the assignment, the assignment engine 208 stores theassignment request or information therefrom in the data store 210 inassociation with the a user profile of the target subject. The method400 is then complete and ends.

FIG. 6 describes an example method 600 for the developing studentgrowth. The method 600 begins at 601, including one or more operationsfor evaluating the time elapsed since a last set of assessments for astudent were generated. The method 600 proceeds to 602, including one ormore operations for utilizing the smart-gradient project (SGP) algorithmto assess and position a student (or student group) into the scaledlearning-progression platform based on the time elapsed. The method 600proceeds to 603, including one or more operations for combining thecomputer-adapted-testing (CAT)+SGP+time-based projection+entry points toestablish the entry point to curriculum. The method 600 proceeds to 604,including one or more operations for normalizing the CAT outcomes withpractice assignments to create an integrated model of mastery againstthe learning progression. The method 600 proceeds to 605, including oneor more operations for extending actual testing using intelligentinferencing based on the relationship of objects within the learningprogression. The method proceeds to 606, including one or moreoperations for utilizing universal skills pool to enable curriculummapping to facilitate lesson planning by mapping to the teacher's chosencurriculum, pacing guide or text book. The method 600 proceeds to 607utilizing a multi-dimensional response item model to bind assignmentsfrom assessment, instruction, and practice assignments into a unifiedscale. The method 600 proceeds to 608, including one or more operationsfor viewing mastery level of students by assignment score, by probedassessment, by general-outcome-measurement (GOM) assessment, and byintegrated models. The method 600 proceeds to 609, including one or moreoperations for enabling the lesson-planning engine to link assessment tocurriculum. The method 600 proceeds to 610, including one or moreoperations for enabling the lesson-planning engine to link assessmentsto government-created learning standards. The method 600 proceeds to611, including one or more operations for including probabilisticalgorithms. The method 600 proceeds to 612, including one or moreoperations for enabling the lesson-planning engine to link assessmentsto instruction resources from many sources. The method 600 proceeds to613, including one or more operations for enabling the lessonplanning-engine to combine assessment sources with standards,curriculums, instructional resources, and assignment delivery systems.The instructions resources include metadata for electronic resources,such as audio files, video files, vector-based files, electronic books,electronic publications, spreadsheets, word processing documents,presentational slides, etc. In some embodiments, the electronicresources may be derived from storage in the data store 410 and/or themedia data store 111 along with metadata describing the contents andcharacteristics of the electronic resources. In other embodiments,metadata for the electronic resources are derived from the electronicresources themselves, for example by parsing header information includedin the electronic resources. In some embodiments, the instructionalmaterials may be retrieved from a resource library database updated toinclude the metadata for the electronic resources, including forexample, data describing the content and characteristics of theelectronic resources and their stored location.

At 612, the lesson-planning engine receives observation data reflectingan observational assessment generated for a target student. In someembodiments, the observation data reflects an answer to a question froman observation template. For example, the observation data can describehow the target subject is performing with reference to a particularskill, requirement, standard, etc. Using the metadata associated withthe electronic resources, the method 600 queries for one or moreelectronic resources that match the observation data. The match can beloose and allow electronic resources that generally pertain to theobservation data to be identified, or may be strict and require that theelectronic resources be precisely directed to the assessment reflectedin the observation data. For example, if the target student isidentified as lacking in his or her ability in a particular area, aloose match may identify resources generally related to what is lacking,and a strict match may identify resources that specifically relate towhat is lacking.

FIG. 7 describes an example method of assessing target students. Theexample method 700 begins at 702 with determining the time elapsed sincea last observation assessment for a target student. The method 700proceeds to 704 for conducting computer-adapted testing for the studentdetermine the educational level of the target student. The method 700proceeds to 706 for determining the student growth percentile. It shouldbe recognized that a student growth percentile, or SGP, compares astudent's growth to that of his or her academic peers nationwide.Academic peers are students in the same grade with similar achievementhistory on standardized assessments. The SGP is reported on a 1-99scale, with lower numbers indicating lower relative growth and highernumbers indicating higher relative growth. For example, a SGP score of90 means the student has shown more growth than 90 percent of students.The percentile rank (PR) and student growth percentile (SGP) are verydifferent metrics has a PR is an achievement score that describes asingle point in time and a SGP is a growth measure that explains studentgrowth between different points in time. Both measures arenorm-referenced, but they have different norming groups. The norminggroup for PR is all students in a particular grade level. The norminggroup for SGP is each student's own academic peer group. Percentile rank(PR) and student growth percentile (SGP) are based on scale of 1-99. Atleast two tests are typically required to report a SGP. The method 700proceeds to 708 to integrate all the scores into a unified score forplacement of the target student by the learning-progression engine.

FIG. 8 describes an example method 800 for generating a lesson plan. Themethod 800 begins and proceeds to 802, including one or more operationsfor generating an expected score for a target (student). The examplemethod 800 proceeds to 804, including one or more operations forgenerating an estimated pace for the target (student). The examplemethod 800 proceeds to 806, including one or more operations for,selecting skills appropriate for the estimated pace for the targetstudent. The example method 800 proceeds to 808, including one or moreoperations for recommending a curriculum for the target student. Theexample method 800 proceeds to the 810, includes one or more operationsfor finding resources that match the curriculum. The example method 800includes one or more operations for generating a lesson plan for thetarget student.

FIG. 9 describes an example method for creating and assigningassignments in accordance with the lesson plan. The example method 900begins and proceeds to 902, at which point the example method receivesan assignment request, generated with by the teacher or the student. Theexample process 900, at 904, includes a preview request for previewingthe resource. If so, the method 900 provides 906 the selected resourcefor the assignment indicated in the preview request for presentation tothe observer. In some embodiments, the electronic resource is providedby the student-growth platform 118 and/or media-distribution server 117via the network 102 to a user/client device 106 of the observer (e.g.,student or teacher). In other embodiments, other entities coupled to thenetwork 102 may provide the electronic resource. By way of example, anobserver who received a list of electronic resources from therecommendation engine 250 via the client application 108 can preview oneor more of the electronic resources to learn more about the resource orresources, determine whether the subject matter of the resource isappropriate for the target subject, etc.

If the method 900 determines at 904 that the request does not include apreview request, the method 900 then determines at 908 whether therequest includes an assignment request that require one or moreelectronic resources for a target subject for completion. If so, themethod 900 determines 910 if any assignment particulars or parametersare associated with the assignment request. In some embodiments, anassignment particular places a condition on how the assignment of anelectronic resource is to be completed. For example, the assignmentparticular may be a due date by which the target must interact with theelectronic resource by. As a further example, if electronic resource isa video, the assignment particular may be a due date by which the targetmust watch the video by using an interface associated with thestudent-growth platform 118. If it is determined at 908 that the requestdoes not include an assignment request for resources, the method 900 isthen complete and ends.

Next, the method 900, at 912, merges the one or more electronicresources with the assignment for the target based on the one or moreassignment particulars or parameters. In some embodiments, the method900 may assign 912 the one or more electronics resources by storing arecord of the assignment in the data store 410 (FIG. 4 ) in associationwith a user profile of the target. The record can include informationdescribing the one or more electronic resources and the one or moreassignment parameters. The method 900 is then complete and ends.

FIGS. 10 and 11 describe an example method 1000 for monitoring andreporting on assignments. The method 1000 begins by monitoring 1002 theprogress of an assignment. The assignment may include the assignment ofone or more electronic resources to a target for completion/interactionby the target subject. The assignment may also include one or moreassignment parameters that dictate how the assignment should becompleted by the target, and the method 1000 can analyze the assignmentparameters to determine if the assignment has been completed. In someembodiments, the reporting platform 232 (FIG. 3 ) is configured tomonitor the status of the assignment, including whether the assignmenthas been fully completed, is in progress, or has not begun.

The method 1000 continues by exchanging 1004 communications between thetarget and the observer of the target. In some embodiments, the method1000 facilitates the exchange by providing the contact information(e.g., an electronic messaging address) of the target to the observerand vice versa. In other embodiments, the method 1000 exchangescommunication by relaying electronic messages between messaging accountsof the target and the observer using an internal messaging service.Exchanging communication using other messaging services, such as email,instant messaging, SMS, etc., is also contemplated. In theseembodiments, the method 1000 may store record of any communicationsexchanged between the target and the observer for later reference andretrieval. Exchanging communication between the observer and the targetis advantageous in a number of respects including that it provides afeedback loop between the target and the observer. For example, thetarget may communicate questions to the observer about what specificareas the target should focus on improving when interacting with anelectronic resource assigned to him/her by the observer, and theobserver may provide feedback to the target. In some embodiments, thecommunications exchanged by the method 1000 may be included in a reportgenerated by the reporting module 232 to summarize the interactionbetween a target and an observer.

Next, the method 1000 determines at 1006 the completion of theassignment. For example, the method 1000 can determine whether theassignment was successfully completed, was never begun, or was inprogress at the conclusion of the time set for completing theassignment. The method 1000 then provides at 1008 the grading frame tothe observer and updates the target profile to reflect the completion.In some embodiments, the reporting module 232 updates a record stored inthe data store 410 with data reflecting the completion.

The method 1000 continues by generating 1010 a report describing thestatus of the assignment and providing it to the observer 1012 and/orother users. The report may include the completion determined by themethod in block 1006, any electronic communication exchanged between thetarget subject in the observer in block 1004, and any other informationabout the assignment, including a description of the electronicresource(s), information from the observation file associated with theassignment, statistics and results from other observational assessmentsperformed previously of the target subject, any related industrystandards, performance benchmarks, requirements, etc.

The method 1000 then determines at 1014 whether the assignment wassuccessfully completed. In some embodiments, this determination is basedon the conclusion from block 1006. If the method 1000 determines at 1014the assignment to have been successfully completed, the method 1000continues by updating the assignment list for the target at 1016 andthen at 1118 generating a status report for the target.

If the method 1000 determines at 1114 the assignment to have not beensuccessfully completed, the method 1000 continues by updating the targetstatus report and then proceeds to generate alerts and report on thetarget. The method 1000 is then complete and ends.

FIG. 12 describes an example method 1200 for the learning-progressionscenario. The method 1200 begins by presenting 1202 an observationtemplate including learning progression questions and associateduser-selectable/definable options to an observer of a target. In someembodiments, the user interface unit 119 (FIG. 1A) displays theobservation template upon receiving interface signals from theobservation engine 221. Next, the method 1200 receives at 1204 userinput providing answers to a question and, based on the answers, themethod 1200 determines at 1206 one or more electronic resources thatrelate to the answer. For example, the user interface unit 119 receivesinput signals providing observation data from the observer via the inputdevice 512 and the assignment manager 260 generates an assignmentrequest based on the observation data and transmits it to the assignmentplayer 264. The assignment manager 260, in reply, identifies one or moreelectronic resources and sends them to the assignment player 264 and theassignment unit 264 instructs the display device 510 to display the oneor more electronic resources to the observer.

The one or more electronic resources are then displayed 1208 by themethod 1200 to the observer. Next, the method 1200 receives 1210 userinput selecting one of the electronic resources, and determines 1212whether the user input includes an instruction to present the resourcefor review for a lesson plan or assignment. If so, the method 1200requests 1214 the electronic resource for presentation. In someembodiments, the method 800 sends a presentation request to the serverhosting the resource requesting the server provide the electronicresource for presentation. For example, the electronic resource is avideo and the assignment player 264 receives a video stream from themedia-distribution server 115 responsive to sending a preview request tothe resource-finder engine 252. If the user input does not include aninstruction to present the resource, the method 1200 continues bydetermining 1216 whether the user input includes an instruction toassign the electronic resource to the target subject for completion. Ifso, the method 1200 requests 1218 the assignment of the electronicresource to the target. In some embodiments, an assignment request issent by the assignment manager 260 to the assignment player 264 via thenetwork 102 requesting the electronic resource be assigned to the targetfor completion. If the method 1200 determines 1216 that the user inputdoes not include an instruction to assign the electronic resource, themethod 1200 is then complete and ends.

FIG. 13 describes an example method 1300 for assessing performance of atarget. The method 1300 begins by receiving 1302 achievement data for attarget student and comparing, at 1304, the achievement data toassessment data and scores associated with the target student. Forexample, the reporting platform 232 may access achievement data from thedata store 113 (by exporting the data by the exporter engine 337) orfrom the third-party server 117 and compare it to observation data alsoaccessed from the data store 113. In some embodiments, the observationdata may be pulled from an associated observation file stored in thedata store 113. Based on the comparison, the method 1300 determines at1306 whether a performance assessment of a target student meets goalsfor the target student and generates at 1308 a report describing theperformance of the target student describing the performance of thetarget student. For example, the reporting platform 232 can generate areport describing the determination it made about the target student'sperformance. The method 1300 provides at 1310 the report for access anddisplay to an administrator, teacher, or other entity, and thencompletes and ends.

It should be understood that the methods 600-1300 are provided by way ofexample, and the variations and combinations of these methods, as wellas other methods, are contemplated. For example, in some embodiments, atleast a portion of the methods 600-1300 represent various segments ofone or more larger methods and may be concatenated or various steps ofthese methods may be combined to produce other methods which areencompassed by the present disclosure. Additionally, it should beunderstood that the assignments of electronic resources and reporting onthe conclusions of the assignments, as described with reference to atleast the methods 600-1300, could be iterative, and thus repeated asmany times as necessary to assist a target student with his or hergrowth and development.

To illustrate various aspects of the system 100 a and the methods600-1300, the following non-limiting example is provided. A school ordistrict administrator or such third party may visit the classrooms ofeach teacher in his/her school to observe. The third party may launchthe client application 108 on his/her wireless client device 106, andonce launched, the observation unit 516 (FIG. 5 ) of the clientapplication 108 may refresh a local repository with updated targetinformation and observation templates received from the observationengine 221 via the network 102. The third party, using an interfacegenerated by the user-interface module 514, may select previouslycompleted observation files for a given student to view how the studentperformed during previous observation sessions.

Example User Interface

Referring now to FIG. 14 , an example observation or user interface (ordashboard display) 1400 for the functionalities of the student-growthplatform 118 is described. It should be understood that the exampleobservation or user interface (or dashboard display) illustrated in FIG.14 is provided merely by way of example, and that other user interfacedisplays (with different criteria or user interactions) may be generatedand displayed by the user/client application 108 to allow users 114 tointeract with the system 100 (a and b) and to allow the system 100 topresent information to the users. For example, various user interfacesmay be produced, to display reports and statistics, display dialogsamong the users (by a chat feature), set parameters and settings, sendelectronic communications, view, listen to and/or interact with theelectronic resources provided by the student-growth platform, etc.

As depicted in FIG. 14 , the observation interface 1400 includes a menuregion 1402 and an observation region 1404. The menu region 1402includes a listing of students belonging to a particular school, class,or group 1406. The menu region 1402 also includes a button 1408 forviewing suggested skills, which may be divided into domains (e.g., fourdomains including foundational skills, language, literature,informational text). The illustrated dashboard shows an example domainliterature. Selecting a student selector 1406 displays a correspondingobservation file created/being created for that particular student. Forexample, in the depicted embodiment, the student selector 1404 for JimBrown has been selected and a corresponding observation file for JimBrown is being populated with assessment information by the observer inthe observation region 1004. Selecting the view suggested skills button1408 creates a new observation file for a student from an observationtemplate. In some embodiments, in response to the selection of theobservation creation button, a dialog (not shown) displaying a list ofusers may be presented to the observer. In some embodiments, the list ofusers represents all of the students that are associated with aparticular school, class, or group within a school. For example, in theeducational setting, the list of users may include all of the studentsin a particular grade in a school, or may be a segmented list ofstudents selected from all of the schools within a school district andtheir corresponding teachers and administrators. In some embodiments,this list is provided on demand to the observation unit 516 by theobservation engine 221 via the network 102 and rendered for display bythe user-interface module 514. In other embodiments, the observationunit 516 may retrieve the list from a local repository and provide it tothe user-interface module 514 for display. Using the user interface, theobserver may then select who the target student is from the list ofusers, and responsive to receiving this input, the user-interface module514 may render the observation interface 1400 for the target studentsimilar to the one displayed in FIG. 14 .

Variation of this observational interface is possible. An observationalinterface may display a dashboard and screenshots that may be specificto a particular subject. In some embodiments, hovering over a standardsbar once a skill is selected displays the standard code and text.Changing the selection to standards view displays the state-specificstandards code; hovering over the code displays the standard's text.

The observation region may include a header region 1410 and a bodyregion 1412. The header region 1010 includes fields for displaying whothe target student of the observation is (e.g., Jim Brown) and whichobservation template is being used for the observation, and forinputting the date and time the observation session was started andcompleted. The header region 1410 also includes an options dialogue boxfor configuring settings, such as generating and sending a report andupdating a user profile. For example, the observer may check a checkboxto set an option for generating and sending a report and for updating auser profile for storage in the data store 113 for later access.

The body region 1412 includes elements for the observer to input his/herassessments made during the observation. For example, as depicted, thebody region 1412 includes a region 1414 indicating the following: createinstructional groups, find instructional resources, and indicate aperformance level. There is a window (which may appear as a pop-up) forteacher activity indicating teacher objectives and lesson, withindicating a sample item.

As depicted, the body region 1412 also includes a resource region 1434for displaying one or more electronic resources. In some embodiments,the electronic resources displayed in the resources region 1434 arereceived from the recommendation engine 250 and displayed in theresource region 1434 responsive to the observer inputting informationinto the answer elements 1416. For example, upon receiving the inputfrom the observer, the observation unit 516 transmits a resource requestto the recommendation engine 250 requesting a list of related electronicresources be provided based on the input (e.g., observation data).

The resource region 1434, as depicted, includes a resource scrollingregion 1418, a scrollbar 1424, one or more electronic resources 1420, aresource description region 1422, an assignment button 1428, a previewbutton 1430, and a due date button 1432. The resource scrolling region1418 provides the user with functionality to scroll through and selectone or more of the various electronic resources displayed therein. Thescrolling can be performed by interacting with the scrollbar 1024 or theresource scrolling region 1018 (e.g., swiping the resource scrollingregion 1018 via a touch-sensitive display with an input element, such asa finger). The selecting can be performed by interacting with therepresentations of the electronic resources in the resource scrollingregion. For example, selecting on an electronic resource once selectsthe resource, and selecting it again unselects the resource. Multipleselection is also possible using known selection methods.

Once one or more resources have been selected by the observer, they canbe previewed or assigned using the corresponding preview and assignmentbuttons 1430 and 1428. In some embodiments, selecting the preview buttontransmits a request for a selected electronic resource, and oncereceived, displays the selected electronic resource(s) in a previewinterface with interface elements allowing the user to view and interactwith the electronic resource. For example, the selected electronicresource is a video and the selecting the preview button displays amedia player for viewing the video.

In some embodiments, selecting the assignment button 1428 sends anassignment request to the assignment unit 518 requesting the assignmentof the one or more selected electronic resources to the target student.In reply, the assignment unit 518 may send a confirmation response tothe assignment unit 518 indicating that the one or more resources weresuccessfully assigned. Once this response has been received, thescrollable resource region may be refreshed to only display theresources that were assigned and the assignment button 1428 may changeto an unassign button to indicate that the displayed resources have beenassigned and provide functionality for the observer to unassign them ifdesired. The due date button is an example of an input element forsetting an assignment parameter. As depicted, when the due date buttonis selected, a calendar dialog is displayed for selecting a date forwhen the assignment of the one or more electronic resources should becompleted. It should be understood that the observation interface 1400could include any number of interface elements for setting assignmentparameters.

In some embodiments, the resource region 1434 may initially be hiddenfrom display until the user inputs observation data into one or more ofthe answer elements 1416. In other embodiments, the resource region 1434may always be displayed, or may be hidden or displayed by selecting acorresponding expansion/contraction button (not shown). While only oneassessment region 1414 and resource region 1434 are displayed in thedepicted embodiment, it should be understood that numerous assessmentregions 1414 and corresponding resource regions 1434 could be included.For example, there could be numerous standards and associatedquestions/indicators for measuring the target subject's performanceduring observation, and thus numerous corresponding resource regions fordisplaying electronic resources that correspond to the variousassessments that have been made by the observer during the observationsession.

An example system and methods for prescribing electronic resources basedon observational assessments have been described. In the abovedescription, for purposes of explanation, numerous specific details areset forth in order to provide a thorough understanding of the presentdisclosure. It should be understood that the technology described in thevarious example embodiments can be practiced without these specificdetails. In other instances, structures and devices are shown in blockdiagram form in order to avoid obscuring the description.

Reference in the present disclosure to “some embodiments,” “anembodiment,” “an example embodiment,” “other embodiments,” etc., meansthat a particular feature, structure, or characteristic described inconnection with the embodiment is included in at least one embodiment ofthe description. The appearances of the phrase “in some embodiments” invarious places in the present disclosure are not necessarily allreferring to the same embodiments.

Some portions of the detailed descriptions that follow are presented interms of algorithms and symbolic representations of operations on databits within a computer memory. These algorithmic descriptions andrepresentations are the means used by those skilled in the dataprocessing arts to most effectively convey the substance of their workto others skilled in the art. An algorithm is here, and generally,conceived to be a self-consistent sequence of steps leading to a desiredresult. The steps are those requiring physical manipulations of physicalquantities. Usually, though not necessarily, these quantities take theform of electrical or magnetic signals capable of being stored,transferred, combined, compared, and otherwise manipulated. It hasproven convenient at times, principally for reasons of common usage, torefer to these signals as bits, values, elements, symbols, characters,terms, numbers, or the like.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise as apparent from the following discussion,it is appreciated that throughout the description, discussions utilizingterms including, for example, “processing” or “computing” or“calculating” or “ranking” or “identifying” or “determining” or“displaying” or “receiving” or “conducting” or “collecting” or the like,refer to the action and processes of a computer system, or similarelectronic computing device, that manipulates and transforms datarepresented as physical (electronic) quantities within the computersystem's registers and memories into other data similarly represented asphysical quantities within the computer system memories or registers orother such information storage, transmission or display devices.

The present embodiment of the present disclosure also relates to anapparatus for performing the operations herein. This apparatus may bespecially constructed for the required purposes, or it may include ageneral-purpose computer selectively activated or reconfigured by acomputer program stored in the computer. Such a computer program may bestored in a computer readable storage medium including, for example, anytype of disk including floppy disks, optical disks, CD-ROMs, andmagnetic disks, read-only memories (ROMs), random access memories(RAMs), EPROMs, EEPROMs, magnetic or optical cards, flash memoriesincluding USB keys with non-volatile memory or any type of mediasuitable for storing electronic instructions, each coupled to a computersystem bus.

The present disclosure can take the form of an entirely hardwareembodiment, an entirely software embodiment or an embodiment containingboth hardware and software elements. In a preferred embodiment, thepresent disclosure is implemented in software, which includes but is notlimited to firmware, resident software, microcode, etc.

Furthermore, the description can take the form of a computer programproduct accessible from a computer-usable or computer-readable mediumproviding program code for use by or in connection with a computer orany instruction execution system. For the purposes of this description,a computer-usable or computer readable medium can be any apparatus thatcan contain, store, communicate, propagate, or transport the program foruse by or in connection with the instruction execution system,apparatus, or device.

A data processing system suitable for storing and/or executing programcode will include at least one processor coupled directly or indirectlyto memory elements through a system bus. The memory elements can includelocal memory employed during actual execution of the program code, bulkstorage, and cache memories which provide temporary storage of at leastsome program code in order to reduce the number of times code must beretrieved from bulk storage during execution.

Input/output or I/O devices (including but not limited to keyboards,displays, pointing devices, etc.) can be coupled to the system eitherdirectly or through intervening I/O controllers.

Network adapters may also be coupled to the system to enable the dataprocessing system to become coupled to other data processing systems orremote printers or storage devices through intervening private or publicnetworks. Modems, cable modems, wireless adapters, and Ethernet cardsare just a few of the currently available types of network adapters.

Finally, the algorithms and displays presented herein are not inherentlyrelated to any particular computer or other apparatus. Variousgeneral-purpose systems may be used with programs in accordance with theteachings herein, or it may prove convenient to construct morespecialized apparatus to perform the required method steps. The requiredstructure for a variety of these systems will appear from thedescription. In addition, the present disclosure is not described withreference to any particular programming language. It will be appreciatedthat a variety of programming languages may be used to implement theteachings of the present disclosure as described herein.

It is intended that the scope of the disclosure be limited not by thisdetailed description, but rather by the claims of this application. Aswill be understood by those familiar with the art, the presentdisclosure may be embodied in other specific forms without departingfrom the spirit or essential characteristics thereof. Likewise, theparticular naming and division of the modules, routines, features,attributes, methodologies and other aspects are not mandatory orsignificant, and the mechanisms that implement the present disclosure orits features may have different names, divisions and/or formats.Furthermore, as will be apparent to one of ordinary skill in therelevant art, the modules, routines, features, attributes, methodologiesand other aspects of the disclosure can be implemented as software,hardware, firmware or any combination of the three. Also, wherever acomponent, an example of which is a module, of the present disclosure isimplemented as software, the component can be implemented as astandalone program, as part of a larger program, as a plurality ofseparate programs, as a statically or dynamically linked library, as akernel loadable module, as a device driver, and/or in every and anyother way. Additionally, the disclosure is in no way limited toimplementation in any specific programming language, or for any specificoperating system or environment. Accordingly, the disclosure is intendedto be illustrative, but not limiting, of the scope of the subject matterset forth in the following claims.

What is claimed is:
 1. A computer-implemented method comprising: a computing platform including a processor coupled to a memory with an executable code, the executable code causing the processor to generate control interface actions, comprising: providing an observation interface, by the processor, for an observer, including an observation region with at least one field receiving input on observation data for a target student and a resource region for displaying one or more projected tasks and electronic resources identified for the target student; providing the observation interface for display on a display device of a computing device of an observer of the target student; receiving an input via displayed observation interface, the input including assessment data reflecting an observational assessment of the target student based on several criteria including 1) time elapsed since a last assessment for the target student based on a standard by a governing entity, 2) computer-adapted testing data performed on the target student, and 3) student-growth percentile data compiled for the target student; prescribing one or more resources based on an observational assessment by the observer; populating the resource region of the observation interface with a plurality of projected tasks and the one or more resources based on positioning of the target student as determined by a learning-progression engine at an entry point for a curriculum identified for the target student based on the observational assessment, the projected tasks created by mapping a specific curriculum by using a universal skills pool; receiving resource data from the one or more resources prescribing one or more recommended electronic instructional resources that provide learning according to a mapped curriculum; updating the resource region of the observation interface using the resource data to include a representation of each of the one or more recommended electronic instructional resources, the resource region further including a user-selectable preview element, operable to preview an electronic resource from the one or more recommended electronic instructional resources, and a user-selectable assignment element, operable to assign at least one electronic resource displayed in the resource region of the observation interface, to the target student for completion; receiving a selection by the observer of the user-selectable assignment element to assign at least one electronic resource of the one or more recommended electronic instructional resources included in the resource region to the target subject for completion; responsive to receiving the selection, designating an assignment of the at least one electronic resource to the target student for completion within a predetermined time; and recording assignment data reflecting the assignment of the at least one electronic resource in a non-transitory data store in association with the target student.
 2. A method comprising: providing an observation engine in a user interface for a target viewer, by a processor, driven by an executable code stored in a memory coupled to the processor, the user interface operable to receive observation input and operable to display information identified for a target student; determining assessment data, by the processor, for the target student, including a level of skills and a pace of learning determined for the target student; identifying, by the processor and the assessment data, a specific curriculum for the target student; mapping, by the processor, a plurality of tasks in accordance with the specific curriculum mapped for the target student; providing a mastery-measurement engine, by the processor, to track at least one of long-term and short-term progress of the target student, by testing data representative of a depth of knowledge on a subject and a scale of cognitive complexity, wherein the mastery-measurement engine is operable to align the assessment data with one or more educational standards; and prescribing, by the processor, one or more recommended electronic resources that facilitate learning according to the mapping and practice tests based on input by the mastery-measurement engine.
 3. The method of claim 2, further comprising: identifying and matching the one or more electronic recommended resources for the specific curriculum, by the processor, and matching associated metadata to one or more aspects of the assessment data reflecting an area in which the target student should receive assignments and learning tasks and recording how the target student is performing in that area.
 4. The method of claim 2, also identifying the one or more electronic recommended resources with the specific curriculum, and wherein the method further comprises: determining, by the processor, how much the target student improved relative to a predetermined standard by utilizing the one or more electronic recommended resources prescribed for the curriculum, and by comparing at least one aspect of performance for the target student with other students at the predetermined standard, by matching student profiles to determine if substantially similar to the target student, wherein the one or more electronic recommended resources include a practice test for the projected tasks, results of the practice test used with computer-adapted testing data to generate an integrated mastery model for the target student.
 5. The method of claim 4, wherein identifying the one or more electronic recommended resources for the target student includes associating the one or more electronic recommended resources with a profile of the target student in the non-transitory data store, and providing an instruction to the target student to interact with the one or more electronic recommended resources.
 6. The method of claim 4, comprising: receiving, by the processor, an assignment parameter associated with an assignment request that indicates a condition that must be met in order for the assignment request to be completed by the target student, wherein assigning the one or more electronic resources to the target student is based at least in part on the assignment parameter.
 7. The method of claim 2, wherein the scale of cognitive complexity comprises at least four levels including, a first level representing recall and reproduction, a second level representing skills and concepts, a third level representing strategic thinking, and a fourth level representing extended thinking.
 8. The method of claim 2, further comprising: determining a mastery designation, by the processor and mastery-measurement engine, for the target student by defining a first criterion to measure mastery of a first skill, defining a second criterion to measure mastery of a sub-skill of the first skill, and determining an improvement measure from the second criterion when the first criterion is not met.
 9. The method of claim 2, comprising: assigning an assignment and monitoring, by the processor, whether the assignment has been completed; generating, by the processor, a report describing whether the assignment has been completed by the target student; and providing the report for display via the observation engine in the user interface, wherein monitoring of assignment completion by the target student includes analyzing interaction data and an assignment parameter associated with the assignment to determine whether the assignment parameter has been satisfied, and the report is generated based on determination regarding the assignment parameter.
 10. The method of claim 2, comprising: a multi-dimensional response item model engine, coupled to the mastery-measurement engine, and operable to receive data from the mastery-measurement engine, and provide an alert indication to at least one of the target viewer and a reporting platform for exporting data externally.
 11. A computer program product comprising a non-transitory computer-usable medium including instructions which, when executed by a computer, cause the computer to: execute an observation engine in a user interface operable to receive observation data on a target student and to display one or more projected tasks and electronic resources identified for the target student; receive an input via the observation engine including observational assessment data on the target student reflecting a skill level of the target student and a pace of learning determined for the target student; identify, by the observational assessment data, a specific curriculum for the target student; mapping, by the computer, a plurality of tasks in accordance with the specific curriculum mapped for the target student; provide a mastery-measurement engine, operable to track at least one of long-term and short-term progress of the target student, by testing data representative of a depth of knowledge on a subject and a scale of cognitive complexity, wherein the mastery-measurement engine is operable to align the assessment data with one or more standards; and prescribe one or more recommended electronic resources that facilitate learning according to the mapping and practice tests based on input by the mastery-measurement engine.
 12. The computer program product of claim 11, wherein the computer program product further provides one or more instructions that cause the computer to identify an electronic resource, by matching metadata associated with the one or more recommended electronic resource to one or more aspects of the assessment data reflecting a specific area for directing assignments and learning tasks to the target student and recording how the target student is performing in said specific area.
 13. The computer program product of claim 12, wherein said electronic resource has associated instructions that further cause the computer to: determine improvement of the target student relative to a predetermined standard by utilizing said electronic resource prescribed for the specific curriculum, and by comparing at least one aspect of performance for the target student with other students at the predetermined standard, by matching student profiles to determine if substantially similar to the target student, wherein the electronic resource includes a practice test for the projected tasks, results of the practice test used with computer-adapted testing data to generate an integrated mastery model for the target student.
 14. The computer program product of claim 12, wherein assigning the electronic resource to the target student includes associating said electronic resource with a profile of the target student in a non-transitory data store, and the assignment is an instruction for the target student to interact with at least one electronic resource.
 15. The computer program product of claim 12, wherein the instructions further cause the computer to: receive an assignment parameter associated with an assignment request that sets a condition that must be met in order for the specific assignment to be completed by the target student, wherein to assign said electronic resource to the target student is based at least in part on the assignment parameter.
 16. The computer program product of claim 11, wherein the scale of cognitive complexity comprises at least four levels including, a first level representing recall and reproduction, a second level representing skills and concepts, a third level representing strategic thinking, and a fourth level representing extended thinking.
 17. The computer program product of claim 11, wherein the instructions further cause the computer to: determine a mastery designation for the target student by defining a first criterion to measure mastery of a first skill, defining a second criterion to measure mastery of a sub-skill of the first skill, and determining an improvement measure from the second criterion when the first criterion is not met.
 18. The computer program product of claim 11, wherein the instructions further cause the computer to: assign and monitor whether an assignment has been completed; generate a report describing whether the assignment has been completed by the target student; and provide the report for display to an observer using the observer engine, wherein the monitoring whether the assignment has been completed by the target student includes analyzing interaction data and an assignment parameter associated with the assignment to determine whether the assignment parameter has been satisfied, and the report is generated based on the determination regarding the assignment parameter.
 19. The computer program product of claim 11, wherein the instructions further cause the computer to: execute a multi-dimensional response item model engine, coupled to the mastery-measurement engine, and operable to receive data from the mastery-measurement engine, and provide an alert indication to at least an observer or a reporting platform for exporting data externally.
 20. A student-growth computing system comprising: a processor; a database associated with the processor, the database operable to collect and store mapping information on a plurality of student users including data representative of relationships among users based on one or more shared attributes, affiliations with institutions, and interests; a user interface coupled to the processor; and a memory with an executable code, wherein the executable code drives the processor to perform control actions to execute: an observation engine in the user interface, operable to provide observation data for a particular student user, display a task, and an electronic resource for a particular student user from the plurality of student users; an assessment engine coupled to the observation engine and operable to receive an observation-assessment data input via the observation engine, based on one or more defined criteria for the particular student user; a mastery-maker engine coupled to the assessment engine and operable to determine a mastery designation for the particular student user and to assign the task including one or more practice tests to enable the particular student user to master a subject interest; and an assignment engine coupled to the processor and responsive to receiving an input from the observation engine, to designate the task, one or more electronic resources, and the one or more practice tests to the particular student user, wherein the task and the one or more practice tests are accessible to the particular student user via a user application provided to the particular student user, the assignment engine operable to provide at least one electronic resource from a media-distribution server based at least in part on a parameter defined for the task. 